{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Identity Resolution with PyDI\n", "\n", "## Learning Objectives\n", "\n", "In this exercise, you will learn how to:\n", "\n", "1. **Implement and Evaluate Blocking Strategies**: Reduce the search space using blocking techniques\n", "2. **Build Rule-Based Matchers**: Create matching rules using similarity comparators\n", "3. **Debug and Refine**: Analyze errors and iteratively improve matching quality\n", "4. **Apply LLM-Based Matching**: Use large language models for entity resolution\n", "\n", "## Entity Matching Problem\n", "\n", "You have two movie datasets with the same schema (after schema mapping):\n", "- **Academy Awards Dataset**: Contains movies that won or were nominated for Academy Awards\n", "- **Actors Dataset**: Contains movies with detailed actor information\n", "\n", "Your goal is to identify which records in these two datasets refer to the same real-world movie. This is challenging because:\n", "- Movie titles may have spelling variations\n", "- Dates may be slightly different\n", "- Director and actor information may be incomplete\n", "- Some movies have very similar titles but are different films" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Setup" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Install the PyDI package. We may regularly push fixes to PyDI, it does not hurt to run this cell regularly!\n", "\n", "In addition to this notebook, check out the [PyDI tutorial notebook](docs/tutorial/PyDI_Tutorial.ipynb) and the [PyDI Wiki](https://github.com/wbsg-uni-mannheim/PyDI/blob/main/docs/wiki/Home.md) for additional methods/information!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#!pip install -qU uma-pydi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PyDI supports two levels of logging: INFO and DEBUG\n", "\n", "It makes sense to use the more verbose DEBUG logging during experimentation and iteration to get more information about what is going on behind the scenes and what parameters you may want/need to change." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import logging\n", "\n", "import os\n", "os.makedirs('logs/', exist_ok=True)\n", "\n", "# choose either default logging or debug logging\n", "\n", "# # Configure logging for INFO level\n", "# logging.basicConfig(\n", "# level=logging.INFO,\n", "# format='[%(levelname)-5s] %(name)s - %(message)s',\n", "# handlers=[\n", "# logging.FileHandler('logs/pydi.log'), # Save to file\n", "# logging.StreamHandler() # Display on console\n", "# ],\n", "# force=True\n", "# )\n", "\n", "# Configure logging for DEBUG level\n", "logging.basicConfig(\n", " level=logging.DEBUG,\n", " format='[%(levelname)-5s] %(name)s - %(message)s',\n", " handlers=[\n", " logging.FileHandler('logs/pydi.log'), # Save to file\n", " logging.StreamHandler() # Display on console\n", " ],\n", " force=True\n", ")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Data directory: c:\\Users\\Ralph\\dev\\pydi\\IR_ex\\data\n", "Output directory: c:\\Users\\Ralph\\dev\\pydi\\IR_ex\\data\\output\n" ] } ], "source": [ "from pathlib import Path\n", "\n", "# Setup directories\n", "DATA_DIR = Path(\"data\")\n", "INPUT_DIR = DATA_DIR / \"input\"\n", "OUTPUT_DIR = DATA_DIR / \"output\"\n", "SPLITS_DIR = DATA_DIR / \"splits\"\n", "\n", "# Create output directory if it doesn't exist\n", "OUTPUT_DIR.mkdir(parents=True, exist_ok=True)\n", "\n", "# Define file paths\n", "ACADEMY_AWARDS_FILE = INPUT_DIR / \"academy_awards.xml\"\n", "ACTORS_FILE = INPUT_DIR / \"actors.xml\"\n", "TRAIN_FILE = SPLITS_DIR / \"train.csv\"\n", "VALIDATION_FILE = SPLITS_DIR / \"validation.csv\"\n", "TEST_FILE = SPLITS_DIR / \"test.csv\"\n", "\n", "print(f\"Data directory: {DATA_DIR.absolute()}\")\n", "print(f\"Output directory: {OUTPUT_DIR.absolute()}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Data Loading and Exploration\n", "\n", "PyDI supports various data loading methods as part of its IO module. As MapForce outputs XML files, we use load_xml.\n", "\n", "You can use the DataFrame.attrs attribute to add meta information to the dataset, e.g. the source of the dataset." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] numexpr.utils - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 16.\n", "[INFO ] numexpr.utils - NumExpr defaulting to 16 threads.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Academy Awards dataset: 4580 records\n", "Actors dataset: 149 records\n", "\n", "Total possible pairs (cartesian product): 682,420\n" ] } ], "source": [ "from PyDI.io import load_xml\n", "\n", "# Load the datasets\n", "df_academy = load_xml(ACADEMY_AWARDS_FILE, name=\"academy_awards\")\n", "\n", "# Add an example source to the dataframe attributes\n", "df_academy.attrs['source'] = 'academyawards'\n", "\n", "df_actors = load_xml(ACTORS_FILE, name=\"actors\")\n", "df_actors.attrs['source'] = 'imdb'\n", "\n", "print(f\"\\nAcademy Awards dataset: {len(df_academy)} records\")\n", "print(f\"Actors dataset: {len(df_actors)} records\")\n", "print(f\"\\nTotal possible pairs (cartesian product): {len(df_academy) * len(df_actors):,}\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "=== Sample records from Academy Awards dataset ===\n" ] }, { "data": { "text/html": [ "
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idtitleactors_actor_namedatedirector_nameoscar
0academy_awards_1BiutifulJavier Bardem2010-01-01NaNNaN
1academy_awards_2True Grit[Jeff Bridges, Hailee Steinfeld]2010-01-01Joel Coen and Ethan CoenNaN
2academy_awards_3The Social NetworkJesse Eisenberg2010-01-01David Fincheryes
3academy_awards_4The King's Speech[Colin Firth, Geoffrey Rush, Helena Bonham Car...2010-01-01Tom Hooperyes
4academy_awards_5127 HoursJames Franco2010-01-01NaNNaN
\n", "
" ], "text/plain": [ " id title \\\n", "0 academy_awards_1 Biutiful \n", "1 academy_awards_2 True Grit \n", "2 academy_awards_3 The Social Network \n", "3 academy_awards_4 The King's Speech \n", "4 academy_awards_5 127 Hours \n", "\n", " actors_actor_name date \\\n", "0 Javier Bardem 2010-01-01 \n", "1 [Jeff Bridges, Hailee Steinfeld] 2010-01-01 \n", "2 Jesse Eisenberg 2010-01-01 \n", "3 [Colin Firth, Geoffrey Rush, Helena Bonham Car... 2010-01-01 \n", "4 James Franco 2010-01-01 \n", "\n", " director_name oscar \n", "0 NaN NaN \n", "1 Joel Coen and Ethan Coen NaN \n", "2 David Fincher yes \n", "3 Tom Hooper yes \n", "4 NaN NaN " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "=== Missing values ===\n", "id 0\n", "title 12\n", "actors_actor_name 3531\n", "date 0\n", "director_name 4172\n", "oscar 3313\n", "dtype: int64\n" ] } ], "source": [ "# Display sample records from Academy Awards\n", "print(\"\\n=== Sample records from Academy Awards dataset ===\")\n", "display(df_academy.head())\n", "\n", "print(\"\\n=== Missing values ===\")\n", "print(df_academy.isnull().sum())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that title and date are the only attributes that are available across most records in the academy_awards dataset. These two attributes will thus be highly important for most matching decisions." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "=== Sample records from Actors dataset ===\n" ] }, { "data": { "text/html": [ "
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idtitleactors_actor_nameactors_actor_birthdayactors_actor_birthplacedate
0actors_17th HeavenJanet Gaynor1906-01-01Pennsylvania1929-01-01
1actors_2CoquetteMary Pickford1892-01-01Canada1930-01-01
2actors_3The DivorceeNorma Shearer1902-01-01Canada1931-01-01
3actors_4Min and BillMarie Dressler1868-01-01Canada1932-01-01
4actors_5The Sin of Madelon ClaudetHelen Hayes1900-01-01Washington DC1933-01-01
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" ], "text/plain": [ " id title actors_actor_name \\\n", "0 actors_1 7th Heaven Janet Gaynor \n", "1 actors_2 Coquette Mary Pickford \n", "2 actors_3 The Divorcee Norma Shearer \n", "3 actors_4 Min and Bill Marie Dressler \n", "4 actors_5 The Sin of Madelon Claudet Helen Hayes \n", "\n", " actors_actor_birthday actors_actor_birthplace date \n", "0 1906-01-01 Pennsylvania 1929-01-01 \n", "1 1892-01-01 Canada 1930-01-01 \n", "2 1902-01-01 Canada 1931-01-01 \n", "3 1868-01-01 Canada 1932-01-01 \n", "4 1900-01-01 Washington DC 1933-01-01 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "=== Missing values ===\n", "id 0\n", "title 0\n", "actors_actor_name 0\n", "actors_actor_birthday 0\n", "actors_actor_birthplace 0\n", "date 0\n", "dtype: int64\n" ] } ], "source": [ "# Display sample records from Actors\n", "print(\"\\n=== Sample records from Actors dataset ===\")\n", "display(df_actors.head())\n", "\n", "print(\"\\n=== Missing values ===\")\n", "print(df_actors.isnull().sum())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load Test and Development Set\n", "\n", "For evaluating identity resolution, we need labeled matching and not matching record pairs. For some tips regarding the creation of these labeled sets, have a look at the slide sets of this exercise and the lecture.\n", "\n", "Each labeled set contains labeled pairs of records:\n", "- **TRUE**: The two records refer to the same movie\n", "- **FALSE**: The two records refer to different movies\n", "\n", "We have three files for this exercise:\n", "- **Training set**: Purpose: train supervised matchers or select few-shot examples for LLMs\n", "- **Validation set**: Purpose: tune parameters and evaluate choices\n", "- **Test set**: Purpose: use for final evaluation" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training set: 150 pairs\n", "Validation set: 147 pairs\n", "Test set: 150 pairs\n" ] } ], "source": [ "import pandas as pd\n", "\n", "TRAIN_FILE = SPLITS_DIR / \"train.csv\"\n", "VALIDATION_FILE = SPLITS_DIR / \"validation.csv\"\n", "TEST_FILE = SPLITS_DIR / \"test.csv\"\n", "\n", "# Load labeled splits\n", "df_train = pd.read_csv(TRAIN_FILE)\n", "df_validation = pd.read_csv(VALIDATION_FILE)\n", "df_test = pd.read_csv(TEST_FILE)\n", "\n", "print(f\"Training set: {len(df_train)} pairs\")\n", "print(f\"Validation set: {len(df_validation)} pairs\")\n", "print(f\"Test set: {len(df_test)} pairs\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Blocking Strategies\n", "\n", "Comparing all possible pairs would require comparing every record in dataset A with every record in dataset B. For large datasets, this is computationally infeasible.\n", "\n", "**Blocking** reduces the search space by only comparing records (candidate pairs) that share some common property (e.g., same first letter of title, similar year). This dramatically reduces the number of comparisons but brings the additional challenge of maintaining high recall (we don't want to miss [m]any true matches).\n", "\n", "Key metrics:\n", "- **Pair Completeness (Recall)**: What % of true matches are included in the candidate pairs?\n", "- **Reduction Ratio**: What % of all possible pairs are eliminated?\n", "- **Pairs Quality**: What % of candidate pairs are true matches?\n", "\n", "PyDI supports the following Blockers:\n", "\n", "1. **StandardBlocker** - Equality-based blocking on one or more key columns.\n", "2. **SortedNeighbourhoodBlocker** - Sorted neighbourhood blocking using a sliding window over a sort key.\n", "3. **TokenBlocker** - Token-based blocking using token overlap on a string column.\n", "4. **EmbeddingBlocker** - Embedding-based blocking using nearest neighbor search over text embeddings." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Standard Blocking\n", "\n", "Let's try using a Standard Blocker first. This implementation uses the first two characters of each word in the title as an aggregated blocking key:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating blocking key values for dataset1: 4580 records\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating blocking key values for dataset2: 149 records\n", "[INFO ] PyDI.entitymatching.blocking.standard.StandardBlocker - created 3586 blocking keys for first dataset\n", "[INFO ] PyDI.entitymatching.blocking.standard.StandardBlocker - created 145 blocking keys for second dataset\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Joining blocking key values: 3586 x 145 blocks\n", "[INFO ] PyDI.entitymatching.blocking.standard.StandardBlocker - created 142 blocks from blocking keys\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Block size distribution:\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Size Frequency\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 92 1\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 14 2\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 10 3\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 5 6\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 4 10\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 4 4\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 3 11\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 2 24\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 2 8\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 2 7\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 2 5\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 1 21\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - 1 18\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Blocking key values:\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - BlockingKeyValue\tFrequency\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - mo\t\t\t24\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ma\t\t\t24\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ca\t\t\t21\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - da\t\t\t18\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - co\t\t\t11\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ch\t\t\t11\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ha\t\t\t11\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - be\t\t\t10\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - sh\t\t\t10\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - pa\t\t\t10\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - su\t\t\t10\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thpi\t\t\t8\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thprof\t\t\t8\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ra\t\t\t7\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thstof\t\t\t7\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - ga\t\t\t6\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thcoof\t\t\t6\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thch\t\t\t6\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - am\t\t\t6\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - thsiof\t\t\t6\n", "[INFO ] PyDI.entitymatching.blocking.standard.StandardBlocker - Debug results written to file: data\\output\\blocking-evaluation\\debugResultsBlocking_StandardBlocker.csv\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating candidate record pairs from 142 blocks\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " Generated: 396 candidates\n" ] }, { "data": { "text/html": [ "
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id1id2
0academy_awards_2actors_120
1academy_awards_2187actors_120
2academy_awards_23actors_17
3academy_awards_733actors_17
4academy_awards_892actors_17
5academy_awards_1532actors_17
6academy_awards_2349actors_17
7academy_awards_3624actors_17
8academy_awards_31actors_79
9academy_awards_3091actors_79
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" ], "text/plain": [ " id1 id2\n", "0 academy_awards_2 actors_120\n", "1 academy_awards_2187 actors_120\n", "2 academy_awards_23 actors_17\n", "3 academy_awards_733 actors_17\n", "4 academy_awards_892 actors_17\n", "5 academy_awards_1532 actors_17\n", "6 academy_awards_2349 actors_17\n", "7 academy_awards_3624 actors_17\n", "8 academy_awards_31 actors_79\n", "9 academy_awards_3091 actors_79" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from PyDI.entitymatching.blocking import StandardBlocker\n", "\n", "# First, we define a function to generate blocking keys\n", "def generate_blocking_key(title):\n", " \"\"\"\n", " Generate blocking key from first 3 words of title.\n", " Takes first 2 chars of each word, concatenates and uppercases.\n", " \"\"\"\n", " if not isinstance(title, str):\n", " return None\n", " \n", " tokens = title.split()\n", " blocking_key = \"\"\n", " \n", " for i in range(min(3, len(tokens))):\n", " blocking_key += tokens[i][:2].upper()\n", " \n", " return blocking_key if blocking_key else None\n", "\n", "# Apply to DataFrames\n", "df_academy['blocking_key'] = df_academy['title'].apply(generate_blocking_key)\n", "df_actors['blocking_key'] = df_actors['title'].apply(generate_blocking_key)\n", "\n", "# Apply standard blocking\n", "blocker_standard = StandardBlocker(\n", " df_academy, df_actors,\n", " on=['blocking_key'],\n", " output_dir=OUTPUT_DIR / \"blocking-evaluation\",\n", " id_column='id'\n", ")\n", "\n", "# Materialize all candidate pairs\n", "candidates_standard = blocker_standard.materialize()\n", "\n", "print()\n", "print(f\" Generated: {len(candidates_standard):,} candidates\")\n", "\n", "# Display sample candidates\n", "display(candidates_standard.head(10))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Blocking Evaluation\n", "\n", "PyDI provides evaluation methods for blocking with pair completeness, pair quality, and reduction ratio as part of the `EntityMatchingEvaluator` class:\n", "- **`evaluate_blocking()`**: Evaluates blocking given an already materialized set of pairs.\n", "- **`evaluate_blocking_batched()`**: Evaluates blocking by iterating over batches and storing results. Useful for very large datasets \n", "\n", "Let's first evaluate our materialized blocking results against our test set." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Pair Completeness: 0.957\n", "[INFO ] root - Pair Quality: 0.114\n", "[INFO ] root - Reduction Ratio: 0.999\n", "[INFO ] root - True Matches Found: 45/47\n", "[INFO ] root - Blocking evaluation complete!\n" ] } ], "source": [ "from PyDI.entitymatching.evaluation import EntityMatchingEvaluator\n", "\n", "# Evaluate blocking quality using validation set\n", "blocking_metrics_standard = EntityMatchingEvaluator.evaluate_blocking(\n", " candidate_pairs=candidates_standard,\n", " blocker=blocker_standard,\n", " test_pairs=df_validation,\n", " out_dir=OUTPUT_DIR / \"blocking-evaluation\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **Task 1**\n", "\n", "Experiment with different blockers:\n", "\n", "- First, use the NoBlocker to see the maximum runtime\n", "- Then, try different blocking keys with the StandardRecordBlocker\n", "- Finally, try the TokenBlocker" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can completely dispense with blocking if your datasets are small enough or you want a baseline to compare your blockers to, by using PyDIs NoBlocker object:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Pair Completeness: 1.000\n", "[INFO ] root - Pair Quality: 0.000\n", "[INFO ] root - Reduction Ratio: 0.000\n", "[INFO ] root - True Matches Found: 47/47\n", "[INFO ] root - Blocking evaluation complete!\n" ] } ], "source": [ "from PyDI.entitymatching.blocking import NoBlocker, TokenBlocker\n", "\n", "blocker_none = NoBlocker(\n", " df_academy, df_actors,\n", " id_column='id' # specify the ID column for both datasets\n", ")\n", "\n", "# but we can also generate the full set of pairs for smaller datasets\n", "candidates_noblocker = blocker_none.materialize()\n", "\n", "# Evaluate blocking quality using test validation set\n", "blocking_metrics_standard = EntityMatchingEvaluator.evaluate_blocking(\n", " candidate_pairs=candidates_noblocker,\n", " blocker=blocker_none,\n", " test_pairs=df_validation,\n", " out_dir=OUTPUT_DIR / \"blocking-evaluation\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Token Blocking\n", "\n", "Now, let's try token blocking:\n", "\n", "Token blocking creates blocks based on individual words or ngrams (tokens) in the title. This is more flexible than standard blocking because:\n", "- Movies with different word order can still be compared\n", "- Multi-word titles are more likely to match" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Creating token index for dataset1: 4580 records\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Creating token index for dataset2: 149 records\n", "[INFO ] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - created 5557 token keys for first dataset\n", "[INFO ] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - created 1036 token keys for second dataset\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Joining token keys: 5557 x 1036 tokens\n", "[INFO ] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - created 1034 blocks from token keys\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Token frequency distribution:\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Size Frequency\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 38 3\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 37 2\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 31 7\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 31 4\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 30 1\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 29 10\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 29 5\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 27 9\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 25 11\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 24 12\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 24 8\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 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1 75\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 1 67\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 1 61\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 1 59\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - 1 50\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Token values:\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Token\t\t\tFrequency\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - the\t\t\t67080\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ing\t\t\t4862\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - and\t\t\t2280\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ter\t\t\t1890\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - man\t\t\t1158\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - her\t\t\t1115\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - all\t\t\t805\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - nth\t\t\t805\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ers\t\t\t804\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - hes\t\t\t756\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - sof\t\t\t755\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - hea\t\t\t705\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ght\t\t\t695\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - est\t\t\t692\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ver\t\t\t660\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ion\t\t\t648\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - oft\t\t\t648\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - ear\t\t\t645\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - fth\t\t\t624\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - hel\t\t\t620\n", "[INFO ] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Debug results written to file: data\\output\\blocking-evaluation\\debugResultsBlocking_TokenBlocker.csv\n", "[DEBUG] PyDI.entitymatching.blocking.token_blocking.TokenBlocker - Creating candidate record pairs from 1034 token blocks\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Applying token blocking on title...\n", "\n", "Generated 110,905 candidate pairs\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Pair Completeness: 1.000\n", "[INFO ] root - Pair Quality: 0.000\n", "[INFO ] root - Reduction Ratio: 0.837\n", "[INFO ] root - True Matches Found: 47/47\n", "[INFO ] root - Blocking evaluation complete!\n" ] } ], "source": [ "from PyDI.entitymatching.blocking import TokenBlocker\n", "\n", "# Apply token blocking\n", "print(\"Applying token blocking on title...\")\n", "blocker_token = TokenBlocker(\n", " df_academy, df_actors,\n", " column='title', # Tokenize titles\n", " output_dir=OUTPUT_DIR / \"blocking-evaluation\",\n", " id_column='id',\n", " ngram_size=3,\n", " ngram_type='character'\n", ")\n", "\n", "candidates_token = blocker_token.materialize()\n", "\n", "print(f\"\\nGenerated {len(candidates_token):,} candidate pairs\")\n", "\n", "# Evaluate blocking quality using validation set\n", "blocking_metrics_standard = EntityMatchingEvaluator.evaluate_blocking(\n", " candidate_pairs=candidates_token,\n", " blocker=blocker_token,\n", " test_pairs=df_validation,\n", " out_dir=OUTPUT_DIR / \"blocking-evaluation\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Depending on your use case and data, different blockers may be more appropriate. Feel free to also try out other blockers like the embedding-based blocker of PyDI!\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Some important things to keep in mind for blocking:\n", "\n", "- Strive for **high reduction ratio** but keep **pair completeness over 97%**!\n", "\n", "- **Your evaluation is only as good as your evaluation set!** You may see 100% pair completeness and assume you do not lose any matches. But that is only true if your evaluation set is \"perfect\"! Do not blindly believe the metrics but use common sense and manually verify that your evaluation set is representative of your matching problem!\n", "\n", "**Important:** While PyDI outputs the \"pair quality\" measure, this measure is only valid if your evaluation set contains ALL possible positive matches. As this is highly unlikely due to the required manual labeling effort, do not try to optimize this metric and do not report it!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Rule-Based Matching with Iterative Refinement\n", "\n", "Now we'll build a rule-based matcher that computes a weighted similarity score for each candidate pair.\n", "\n", "We'll start with a simple matcher using:\n", "- **Title similarity**: Levensthein similarity on titles\n", "- **Date similarity**: Numeric tolerance (within 2 years)\n", "\n", "Additional comparators are defined but commented out. You can uncomment them during refinement to try to increase the matching score." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "from PyDI.entitymatching.comparators import StringComparator, DateComparator\n", "\n", "# Define comparators\n", "comparators = [\n", " StringComparator(column=\"title\",\n", " similarity_function=\"levenshtein\",\n", " preprocess=str.lower\n", " ),\n", " DateComparator(\n", " column=\"date\", \n", " max_days_difference=730 # 2 year tolerance (2*365 days)\n", " ),\n", "]\n", "\n", "# define the weights for the comparators\n", "weights = [0.5, 0.5]\n", "# define the similarity threshold of the rule for deciding on a match\n", "threshold = 0.6\n", "\n", "# Uncomment these and add them to the list during refinement based on debug analysis\n", "# StringComparator(column=\"title\", similarity_function=\"jaccard\", tokenization=\"word\", preprocess=str.lower), # Token similarity\n", "# StringComparator(column=\"director\", similarity_function=\"jaccard\", tokenization=\"word\", preprocess=str.lower), # Director name\n", "# StringComparator(column=\"director\", similarity_function=\"levenshtein\", preprocess=str.lower), # Director with edit distance\n", "# StringComparator(column=\"actors\", similarity_function=\"jaccard\", tokenization=\"word\", list_strategy=\"best_match\", preprocess=str.lower), # Best actor match\n", "# DateComparator(column=\"date\", max_days_difference=365), # less lenient date matching (1 year)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we initialize the rule-based matcher and activate the Debug mode of the matcher. When Debug mode is active, PyDI writes detailed debug logs into the output, which we can subsequently use to refine the matching results.\n", "\n", "Another important parameter of all matchers is `candidates`. We can either pass a set of already materialized candidates, e.g. `candidates_standard` from before. But as datasets are usually large, it makes more sense to pass the blocker directly - the matcher will then internally run the blocking on batches instead of fully materializing all pairs at once. You can control the size of the batches when initializing the blocker with the `batch_size` parameter." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Starting Entity Matching\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Blocking 4580 x 149 elements\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating candidate record pairs from 142 blocks\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Matching 4580 x 149 elements after 0:00:0.003; 396 blocked pairs (reduction ratio: 0.9994197122006975)\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating candidate record pairs from 142 blocks\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Entity Matching finished after 0:00:0.189; found 134 correspondences.\n" ] } ], "source": [ "from PyDI.entitymatching import RuleBasedMatcher\n", "\n", "# Initialize matcher\n", "matcher = RuleBasedMatcher()\n", "\n", "# Run matching with debug mode enabled\n", "correspondences, debug_info = matcher.match(\n", " df_left=df_academy,\n", " df_right=df_actors,\n", " candidates=blocker_standard,\n", " id_column='id',\n", " comparators=comparators,\n", " weights=weights,\n", " threshold=threshold,\n", " debug=True\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can evaluate the result of our entity matching with this method of the EntityMatchingEvaluator:\n", "- **`evaluate_matching()`**: Evaluates matching given an evaluation set and the predicted correspondences. " ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[DEBUG] root - Individual correspondence evaluations:\n", "[DEBUG] root - [correct] academy_awards_2187,actors_120,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2732,actors_110,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2040,actors_46,TRUE,sim:0.7493\n", "[DEBUG] root - [correct] academy_awards_503,actors_148,TRUE,sim:1.0000\n", "[DEBUG] root - [correct] academy_awards_1430,actors_132,TRUE,sim:0.7493\n", "[DEBUG] root - [correct] academy_awards_608,actors_146,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_618,actors_73,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_723,actors_71,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2892,actors_29,TRUE,sim:0.7493\n", "[DEBUG] root - [correct] academy_awards_902,actors_141,TRUE,sim:0.7083\n", "[DEBUG] root - [correct] academy_awards_910,actors_68,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3244,actors_101,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_1272,actors_135,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_1776,actors_51,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_1541,actors_56,TRUE,sim:0.7167\n", "[DEBUG] root - [correct] academy_awards_1633,actors_54,TRUE,sim:0.7255\n", "[DEBUG] root - [correct] academy_awards_1880,actors_126,TRUE,sim:0.7339\n", "[DEBUG] root - [correct] academy_awards_1943,actors_48,TRUE,sim:0.7177\n", "[DEBUG] root - [correct] academy_awards_1995,actors_47,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2141,actors_44,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2288,actors_40,TRUE,sim:0.7321\n", "[DEBUG] root - [correct] academy_awards_2334,actors_39,TRUE,sim:0.7177\n", "[DEBUG] root - [correct] academy_awards_2566,actors_113,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3713,actors_94,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2620,actors_112,TRUE,sim:0.7262\n", "[DEBUG] root - [correct] academy_awards_2625,actors_34,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_2686,actors_33,TRUE,sim:0.7493\n", "[DEBUG] root - [correct] academy_awards_2844,actors_30,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3187,actors_24,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3252,actors_23,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3300,actors_100,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3423,actors_20,TRUE,sim:0.7262\n", "[DEBUG] root - [correct] academy_awards_3488,actors_19,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_3813,actors_93,TRUE,sim:0.7500\n", "[DEBUG] root - [correct] academy_awards_4140,actors_89,TRUE,sim:0.7500\n", "[DEBUG] root - [wrong] academy_awards_4520,actors_80,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4500,actors_3,TRUE,sim:0.5000\n", "[DEBUG] root - [missing] academy_awards_1392,actors_59,TRUE,sim:N/A\n", "[DEBUG] root - [wrong] academy_awards_4399,actors_6,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4444,actors_83,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4491,actors_81,TRUE,sim:0.5000\n", "[DEBUG] root - [missing] academy_awards_4270,actors_9,TRUE,sim:N/A\n", "[DEBUG] root - [wrong] academy_awards_4446,actors_5,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4397,actors_85,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4475,actors_4,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4442,actors_84,TRUE,sim:0.5000\n", "[DEBUG] root - [wrong] academy_awards_4529,actors_2,TRUE,sim:0.5000\n", "[DEBUG] root - [correct] academy_awards_1844,actors_126,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1983,actors_47,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3665,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4021,actors_89,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2239,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1202,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1092,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3846,actors_92,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_688,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2987,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_531,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1070,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2991,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1196,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1182,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2990,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4242,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1591,actors_129,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_508,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_642,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_624,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4453,actors_81,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2233,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3896,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2244,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1215,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4486,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2556,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1212,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2857,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4065,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2864,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_918,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_322,actors_151,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2,actors_120,FALSE,sim:0.5000\n", "[DEBUG] root - [correct] academy_awards_2679,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3933,actors_83,FALSE,sim:0.5000\n", "[DEBUG] root - [correct] academy_awards_3876,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1115,actors_101,FALSE,sim:0.5000\n", "[DEBUG] root - [correct] academy_awards_4059,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4440,actors_82,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3297,actors_100,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1175,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1443,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1220,actors_135,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3117,actors_25,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_290,actors_78,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2386,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1286,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1348,actors_133,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_913,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2595,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1475,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3676,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1285,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4472,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_945,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_941,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1726,actors_52,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4033,actors_90,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2692,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3730,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3333,actors_21,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_693,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2797,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2033,actors_46,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2207,actors_42,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2541,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2981,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2457,actors_36,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_439,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3927,actors_91,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_622,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3761,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3035,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_403,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3679,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2822,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4263,actors_86,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4190,actors_9,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1645,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4229,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1312,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_872,actors_141,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3055,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_910,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2959,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3221,actors_23,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2433,actors_115,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2835,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2902,actors_28,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1478,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2353,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3198,actors_101,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2543,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2328,actors_39,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4232,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1650,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2588,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1062,actors_65,FALSE,sim:N/A\n", "[INFO ] root - Debug results written to data\\output\\debug_results_entity_matching\\debugResultsMatchingRule.csv and data\\output\\debug_results_entity_matching\\debugResultsMatchingRule.csv_short\n", "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 35\n", "[INFO ] root - True Negatives: 100\n", "[INFO ] root - False Positives: 0\n", "[INFO ] root - False Negatives: 12\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.918\n", "[INFO ] root - Precision: 1.000\n", "[INFO ] root - Recall: 0.745\n", "[INFO ] root - F1-Score: 0.854\n" ] } ], "source": [ "debug_output_dir = OUTPUT_DIR / \"debug_results_entity_matching\"\n", "debug_output_dir.mkdir(parents=True, exist_ok=True)\n", "\n", "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=correspondences,\n", " test_pairs=df_validation,\n", " out_dir=debug_output_dir,\n", " debug_info=debug_info, # add debug info (optional)\n", " matcher_instance=matcher # add matcher instance for context for debug files (optional)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cluster Consistency Analysis\n", "\n", "Let's analyze the **cluster structure** to identify any inconsistencies our imperfect evaluation set may miss. The EntityMatchingEvaluator offers the `create_cluster_size_distribution` method for this purpose." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Cluster Size Distribution of 132 clusters:\n", "[INFO ] root - \tCluster Size\t| Frequency\t| Percentage\n", "[INFO ] root - \t──────────────────────────────────────────────────\n", "[INFO ] root - \t\t2\t|\t130\t|\t98.48%\n", "[INFO ] root - \t\t3\t|\t2\t|\t1.52%\n", "[INFO ] root - Cluster size distribution written to data\\output\\cluster_analysis\\cluster_size_distribution.csv\n" ] } ], "source": [ "# Create cluster size distribution from our matches\n", "cluster_distribution = EntityMatchingEvaluator.create_cluster_size_distribution(\n", " correspondences=correspondences,\n", " out_dir=OUTPUT_DIR / \"cluster_analysis\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Remember: **Your evaluation is only as good as your evaluation set!** This is also true for the matching step! You see an F1 of 95% and you are happy, but if the evaluation set does not accurately represent your data, the cluster size distribution is one way you can spot this. Seeing many clusters with a size larger than 2 when you are sure your source datasets are deduplicated should make you question for evaluation set and manually check what is going on!\n", "\n", "- In this stage of the project, you will **iteratively refine your evaluation sets** not only based on the metrics you see but also manual inspection of debug logs and cluster size distribution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Post-Processing: Global Matching\n", "\n", "#### The One-to-One Constraint\n", "\n", "In identity resolution, we often want to enforce a **one-to-one constraint**: each record in dataset A should match at most one record in dataset B, and vice versa. It only makes sense to enforce this constraint if you are sure that your source datasets are themselves duplicate-free!\n", "\n", "Our current results may violate this constraint (one movie in Academy Awards might match multiple movies in Actors database), so enforcing it can still improve the results\n", "\n", "PyDI offers the following methods for global matching:\n", "\n", "- **GreedyOneToOneMatchingAlgorithm**: Ensures one-to-one matching by greedily selecting highest-scoring correspondences while avoiding conflicts.\n", "- **MaximumBipartiteMatching**: Finds optimal one-to-one matching using maximum weight bipartite matching algorithms.\n", "- **StableMatching**: Finds stable matches where records are matched to mutually preferred partners, ensuring no record would prefer to switch." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Filtered correspondences: 134 -> 134 (threshold=0.0)\n", "[INFO ] root - Greedy matching: 134 -> 132 correspondences (264 entities matched)\n", "[INFO ] root - GreedyOneToOneMatchingAlgorithm: 134 -> 132 correspondences\n", "[INFO ] root - GreedyOneToOneMatchingAlgorithm: 266 -> 264 entities\n", "[INFO ] root - Cluster Size Distribution of 132 clusters:\n", "[INFO ] root - \tCluster Size\t| Frequency\t| Percentage\n", "[INFO ] root - \t──────────────────────────────────────────────────\n", "[INFO ] root - \t\t2\t|\t132\t|\t100.00%\n", "[INFO ] root - Cluster size distribution written to data\\output\\cluster_analysis\\cluster_size_distribution.csv\n" ] } ], "source": [ "from PyDI.entitymatching import GreedyOneToOneMatchingAlgorithm, StableMatching, MaximumBipartiteMatching\n", "\n", "one_to_one_algorithm = GreedyOneToOneMatchingAlgorithm()\n", "refined_correspondences = one_to_one_algorithm.cluster(correspondences)\n", "\n", "# Create cluster size distribution from our matches\n", "cluster_distribution = EntityMatchingEvaluator.create_cluster_size_distribution(\n", " correspondences=refined_correspondences,\n", " out_dir=OUTPUT_DIR / \"cluster_analysis\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **Task 2**\n", "\n", "1. Understand the results\n", " - Inspect the log files in data\\output to see which errors were made\n", "2. Try different combinations of comparators or weights in your matching rule\n", " - Can you improve the performance?\n", " - Can you improve the performance using global matching?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When inspecting the debug log, we can see that the year information in both datasets is not reliable and we are missing many actual matches due to a low overall similarity caused by the year comparator. Let's try giving more weight to the title comparator based on our inspection:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Starting Entity Matching\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Blocking 4580 x 149 elements\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating candidate record pairs from 142 blocks\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Matching 4580 x 149 elements after 0:00:0.002; 396 blocked pairs (reduction ratio: 0.9994197122006975)\n", "[DEBUG] PyDI.entitymatching.blocking.standard.StandardBlocker - Creating candidate record pairs from 142 blocks\n", "[INFO ] PyDI.entitymatching.rule_based.RuleBasedMatcher - Entity Matching finished after 0:00:0.160; found 154 correspondences.\n", "[DEBUG] root - Individual correspondence evaluations:\n", "[DEBUG] root - [wrong] academy_awards_2,actors_120,FALSE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_2187,actors_120,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_4529,actors_2,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_2732,actors_110,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2040,actors_46,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_4442,actors_84,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_503,actors_148,TRUE,sim:1.0000\n", "[DEBUG] root - [correct] academy_awards_1430,actors_132,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_608,actors_146,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_618,actors_73,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_723,actors_71,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2892,actors_29,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_902,actors_141,TRUE,sim:0.7917\n", "[DEBUG] root - [correct] academy_awards_910,actors_68,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_4446,actors_5,TRUE,sim:0.7000\n", "[DEBUG] root - [wrong] academy_awards_1115,actors_101,FALSE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_3244,actors_101,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1272,actors_135,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1776,actors_51,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1541,actors_56,TRUE,sim:0.8033\n", "[DEBUG] root - [correct] academy_awards_4491,actors_81,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_1633,actors_54,TRUE,sim:0.8163\n", "[DEBUG] root - [correct] academy_awards_1880,actors_126,TRUE,sim:0.8274\n", "[DEBUG] root - [correct] academy_awards_1943,actors_48,TRUE,sim:0.8048\n", "[DEBUG] root - [correct] academy_awards_1995,actors_47,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2141,actors_44,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2288,actors_40,TRUE,sim:0.8250\n", "[DEBUG] root - [correct] academy_awards_2334,actors_39,TRUE,sim:0.8048\n", "[DEBUG] root - [correct] academy_awards_2566,actors_113,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3713,actors_94,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2620,actors_112,TRUE,sim:0.8167\n", "[DEBUG] root - [correct] academy_awards_2625,actors_34,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2686,actors_33,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_2844,actors_30,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3187,actors_24,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3252,actors_23,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3300,actors_100,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3423,actors_20,TRUE,sim:0.8167\n", "[DEBUG] root - [wrong] academy_awards_3933,actors_83,FALSE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4444,actors_83,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_3488,actors_19,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3813,actors_93,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_4140,actors_89,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_4397,actors_85,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4399,actors_6,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4475,actors_4,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4500,actors_3,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4520,actors_80,TRUE,sim:0.7000\n", "[DEBUG] root - [missing] academy_awards_1392,actors_59,TRUE,sim:N/A\n", "[DEBUG] root - [missing] academy_awards_4270,actors_9,TRUE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1844,actors_126,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1983,actors_47,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3665,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4021,actors_89,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2239,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1202,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1092,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3846,actors_92,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_688,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2987,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_531,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1070,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2991,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1196,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1182,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2990,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4242,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1591,actors_129,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_508,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_642,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_624,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4453,actors_81,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2233,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3896,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2244,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1215,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4486,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2556,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1212,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2857,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4065,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2864,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_918,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_322,actors_151,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2679,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3876,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4059,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4440,actors_82,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3297,actors_100,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1175,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1443,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1220,actors_135,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3117,actors_25,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_290,actors_78,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2386,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1286,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1348,actors_133,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_913,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2595,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1475,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3676,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1285,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4472,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_945,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_941,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1726,actors_52,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4033,actors_90,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2692,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3730,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3333,actors_21,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_693,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2797,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2033,actors_46,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2207,actors_42,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2541,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2981,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2457,actors_36,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_439,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3927,actors_91,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_622,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3761,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3035,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_403,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3679,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2822,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4263,actors_86,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4190,actors_9,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1645,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4229,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1312,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_872,actors_141,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3055,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_910,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2959,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3221,actors_23,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2433,actors_115,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2835,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2902,actors_28,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1478,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2353,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3198,actors_101,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2543,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2328,actors_39,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4232,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1650,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2588,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1062,actors_65,FALSE,sim:N/A\n", "[INFO ] root - Debug results written to data\\output\\debug_results_entity_matching\\debugResultsMatchingRule.csv and data\\output\\debug_results_entity_matching\\debugResultsMatchingRule.csv_short\n", "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 45\n", "[INFO ] root - True Negatives: 97\n", "[INFO ] root - False Positives: 3\n", "[INFO ] root - False Negatives: 2\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.966\n", "[INFO ] root - Precision: 0.938\n", "[INFO ] root - Recall: 0.957\n", "[INFO ] root - F1-Score: 0.947\n" ] } ], "source": [ "# Run matching with adjusted weights\n", "correspondences, debug_info = matcher.match(\n", " df_left=df_academy,\n", " df_right=df_actors,\n", " candidates=blocker_standard,\n", " id_column='id',\n", " comparators=comparators,\n", " weights=[0.7, 0.3], # increase weight on title based on debug analysis\n", " threshold=threshold,\n", " debug=True\n", ")\n", "\n", "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=correspondences,\n", " test_pairs=df_validation,\n", " out_dir=debug_output_dir,\n", " debug_info=debug_info, # add debug info (optional)\n", " matcher_instance=matcher # add matcher instance for context for debug files (optional)\n", ")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Cluster Size Distribution of 144 clusters:\n", "[INFO ] root - \tCluster Size\t| Frequency\t| Percentage\n", "[INFO ] root - \t──────────────────────────────────────────────────\n", "[INFO ] root - \t\t2\t|\t135\t|\t93.75%\n", "[INFO ] root - \t\t3\t|\t8\t|\t5.56%\n", "[INFO ] root - \t\t4\t|\t1\t|\t0.69%\n", "[INFO ] root - Cluster size distribution written to data\\output\\cluster_analysis\\cluster_size_distribution.csv\n" ] } ], "source": [ "# Create cluster size distribution from our matches\n", "cluster_distribution = EntityMatchingEvaluator.create_cluster_size_distribution(\n", " correspondences=correspondences,\n", " out_dir=OUTPUT_DIR / \"cluster_analysis\"\n", ")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Filtered correspondences: 154 -> 154 (threshold=0.0)\n", "[INFO ] root - Greedy matching: 154 -> 144 correspondences (288 entities matched)\n", "[INFO ] root - GreedyOneToOneMatchingAlgorithm: 154 -> 144 correspondences\n", "[INFO ] root - GreedyOneToOneMatchingAlgorithm: 298 -> 288 entities\n", "[DEBUG] root - Individual correspondence evaluations:\n", "[DEBUG] root - [correct] academy_awards_503,actors_148,TRUE,sim:1.0000\n", "[DEBUG] root - [correct] academy_awards_2187,actors_120,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_910,actors_68,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_723,actors_71,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_618,actors_73,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_608,actors_146,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2732,actors_110,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_4140,actors_89,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3300,actors_100,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3252,actors_23,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3488,actors_19,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1776,actors_51,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1272,actors_135,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3244,actors_101,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2141,actors_44,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_1995,actors_47,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3813,actors_93,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2625,actors_34,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3187,actors_24,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2844,actors_30,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_3713,actors_94,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2566,actors_113,TRUE,sim:0.8500\n", "[DEBUG] root - [correct] academy_awards_2686,actors_33,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_2040,actors_46,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_1430,actors_132,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_2892,actors_29,TRUE,sim:0.8496\n", "[DEBUG] root - [correct] academy_awards_1880,actors_126,TRUE,sim:0.8274\n", "[DEBUG] root - [correct] academy_awards_2288,actors_40,TRUE,sim:0.8250\n", "[DEBUG] root - [correct] academy_awards_2620,actors_112,TRUE,sim:0.8167\n", "[DEBUG] root - [correct] academy_awards_3423,actors_20,TRUE,sim:0.8167\n", "[DEBUG] root - [correct] academy_awards_1633,actors_54,TRUE,sim:0.8163\n", "[DEBUG] root - [correct] academy_awards_1943,actors_48,TRUE,sim:0.8048\n", "[DEBUG] root - [correct] academy_awards_2334,actors_39,TRUE,sim:0.8048\n", "[DEBUG] root - [correct] academy_awards_1541,actors_56,TRUE,sim:0.8033\n", "[DEBUG] root - [correct] academy_awards_902,actors_141,TRUE,sim:0.7917\n", "[DEBUG] root - [correct] academy_awards_4442,actors_84,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4529,actors_2,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4491,actors_81,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4446,actors_5,TRUE,sim:0.7000\n", "[DEBUG] root - [wrong] academy_awards_3933,actors_83,FALSE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4475,actors_4,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4397,actors_85,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4399,actors_6,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4520,actors_80,TRUE,sim:0.7000\n", "[DEBUG] root - [correct] academy_awards_4500,actors_3,TRUE,sim:0.7000\n", "[DEBUG] root - [missing] academy_awards_1392,actors_59,TRUE,sim:N/A\n", "[DEBUG] root - [missing] academy_awards_4444,actors_83,TRUE,sim:N/A\n", "[DEBUG] root - [missing] academy_awards_4270,actors_9,TRUE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1844,actors_126,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1983,actors_47,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3665,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4021,actors_89,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2239,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1202,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1092,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3846,actors_92,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_688,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2987,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_531,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1070,actors_65,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2991,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1196,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1182,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2990,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4242,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1591,actors_129,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_508,actors_148,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_642,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_624,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4453,actors_81,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2233,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3896,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2244,actors_40,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1215,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4486,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2556,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1212,actors_136,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2857,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4065,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2864,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_918,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_322,actors_151,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2,actors_120,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2679,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3876,actors_14,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1115,actors_101,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4059,actors_12,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4440,actors_82,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3297,actors_100,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1175,actors_62,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1443,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1220,actors_135,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3117,actors_25,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_290,actors_78,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2386,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1286,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1348,actors_133,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_913,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2595,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1475,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3676,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1285,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4472,actors_80,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_945,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_941,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1726,actors_52,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4033,actors_90,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2692,actors_110,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3730,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3333,actors_21,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_693,actors_71,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2797,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2033,actors_46,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2207,actors_42,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2541,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2981,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2457,actors_36,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_439,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3927,actors_91,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_622,actors_145,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3761,actors_15,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3035,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_403,actors_149,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3679,actors_16,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2822,actors_108,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4263,actors_86,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4190,actors_9,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1645,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4229,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1312,actors_134,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_872,actors_141,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3055,actors_104,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_910,actors_67,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2959,actors_105,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3221,actors_23,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2433,actors_115,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2835,actors_107,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2902,actors_28,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1478,actors_131,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2353,actors_38,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_3198,actors_101,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2543,actors_113,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2328,actors_39,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_4232,actors_87,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1650,actors_128,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_2588,actors_34,FALSE,sim:N/A\n", "[DEBUG] root - [correct] academy_awards_1062,actors_65,FALSE,sim:N/A\n", "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 44\n", "[INFO ] root - True Negatives: 99\n", "[INFO ] root - False Positives: 1\n", "[INFO ] root - False Negatives: 3\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.973\n", "[INFO ] root - Precision: 0.978\n", "[INFO ] root - Recall: 0.936\n", "[INFO ] root - F1-Score: 0.957\n" ] } ], "source": [ "refined_correspondences = one_to_one_algorithm.cluster(correspondences)\n", "\n", "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=refined_correspondences,\n", " test_pairs=df_validation,\n", " out_dir=debug_output_dir\n", ")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Cluster Size Distribution of 144 clusters:\n", "[INFO ] root - \tCluster Size\t| Frequency\t| Percentage\n", "[INFO ] root - \t──────────────────────────────────────────────────\n", "[INFO ] root - \t\t2\t|\t144\t|\t100.00%\n", "[INFO ] root - Cluster size distribution written to data\\output\\cluster_analysis\\cluster_size_distribution.csv\n" ] } ], "source": [ "# Create cluster size distribution from our matches\n", "cluster_distribution = EntityMatchingEvaluator.create_cluster_size_distribution(\n", " correspondences=refined_correspondences,\n", " out_dir=OUTPUT_DIR / \"cluster_analysis\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once we have optimized all parameters on the validation set, we can verify the performance of our rule on out held-out test set" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 49\n", "[INFO ] root - True Negatives: 100\n", "[INFO ] root - False Positives: 0\n", "[INFO ] root - False Negatives: 1\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.993\n", "[INFO ] root - Precision: 1.000\n", "[INFO ] root - Recall: 0.980\n", "[INFO ] root - F1-Score: 0.990\n" ] } ], "source": [ "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=refined_correspondences,\n", " test_pairs=df_test,\n", " out_dir=debug_output_dir\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### **Task 3 (Optional)**\n", "\n", "Check out the MLBasedMatcher in the [PyDI tutorial notebook](docs/tutorial/PyDI_Tutorial.ipynb) and apply scikit learn models to try to achieve a better result by automatically learning the weights of the matching rule." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6. LLM-Based Matching\n", "\n", "Large Language Models (LLMs) can perform entity resolution by:\n", "- Understanding semantic similarity beyond string matching\n", "- Handling variations in formatting, spelling, and abbreviations\n", "- Reasoning about context (e.g., actor names, directors, dates)\n", "\n", "We'll use **GPT-5-nano** via PyDI's `LLMBasedMatcher` to match the same candidate pairs and compare results to our RuleBasedMatcher. The LLM-based matcher internally uses a pre-defined prompt for entity matching. You can provide your own by providing the `system_prompt` parameter.\n", "\n", "**Note**: This will make API calls and incur costs." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OPENAI_API_KEY found in environment\n", " Key starts with: sk-proj-Q4...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" ] }, { "data": { "text/plain": [ "AIMessage(content='I’m doing well, thanks! How about you? What can I help you with today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 28, 'prompt_tokens': 12, 'total_tokens': 40, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-5-nano-2025-08-07', 'system_fingerprint': None, 'id': 'chatcmpl-CTPeACIY0yAQGFa18IPwundREjcv6', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--071caffd-fdb5-4e39-8acb-7fd9ea5e9640-0', usage_metadata={'input_tokens': 12, 'output_tokens': 28, 'total_tokens': 40, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Lets setup our chat model\n", "#from langchain_groq import ChatGroq\n", "from langchain_openai import ChatOpenAI\n", "\n", "from dotenv import load_dotenv\n", "import os\n", "\n", "load_dotenv()\n", "\n", "# Check for OpenAI API key\n", "api_key = os.getenv('OPENAI_API_KEY')\n", "if api_key:\n", " print(\"OPENAI_API_KEY found in environment\")\n", " print(f\" Key starts with: {api_key[:10]}...\")\n", "else:\n", " print(\"OPENAI_API_KEY not found in environment\")\n", "\n", "# set back to info logging to avoid spam from other libraries\n", "logging.getLogger().setLevel(logging.INFO) \n", "\n", "\n", "# Initialize OpenAI chat model\n", "chat_model = ChatOpenAI(\n", " model=\"gpt-5-nano\", \n", " max_tokens=500, # Reasonable limit for structured output\n", " temperature=0.0, # Deterministic output\n", " reasoning_effort=\"minimal\", \n", ")\n", "\n", "chat_model.invoke(\"How are you doing today?\")" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "from PyDI.entitymatching import LLMBasedMatcher\n", "\n", "# Initialize LLM-based matcher\n", "llm_matcher = LLMBasedMatcher()\n", "\n", "# Define fields to include in LLM prompts\n", "attributes_for_llm = ['title', 'date']" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Entity matching: academy_awards (4580 records) <-> actors (149 records)\n", "[INFO ] root - Processing 1 candidate batches\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Running LLM-based matching...\n", "\n", "(This may take several minutes depending on the number of candidates)\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:28.325169Z\", \"row_index\": 0, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2519.7436809539795, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Same title but different dates likely refer to different films; insufficient overlap to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:30.701304Z\", \"row_index\": 1, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2372.1349239349365, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 51, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title 'True Grit' with different dates; could refer to different editions or releases but likely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:32.594277Z\", \"row_index\": 2, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1889.9707794189453, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 49, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gasland\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different (Gasland vs Gaslight) and dates refer to different works, unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:33.979061Z\", \"row_index\": 3, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1380.784273147583, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gattaca\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and release years; no overlap indicating same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:35.962761Z\", \"row_index\": 4, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1980.6997776031494, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 44, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gagarin\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no evidence they refer to the same work or entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:37.516304Z\", \"row_index\": 5, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1550.5402088165283, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 43, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gandhi\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and entirely different dates; no clear linkage between the two records.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:39.667935Z\", \"row_index\": 6, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2148.6334800720215, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 45, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gambit\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates suggest different works; no strong overlap to indicate the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:41.420782Z\", \"row_index\": 7, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1749.8481273651123, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Both records share the same title; dates differ by one year which could reflect production/release year variations for the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:42.943532Z\", \"row_index\": 8, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1518.7489986419678, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 57, \"total_tokens\": 276, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Warriors of Qiugang\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Way of All Flesh & The Las\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works (The Warriors of Qiugang vs The Way of All Flesh & The Las) and non-overlapping years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:44.446660Z\", \"row_index\": 9, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1500.1277923583984, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 45, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The War of the Worlds\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Way of All Flesh & The Las\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are different; no clear overlap in information to indicate the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:46.651634Z\", \"row_index\": 10, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2201.9739151000977, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coraline\\\", \\\"date\\\": \\\"2009-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates; no basis to link to the same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:48.188583Z\", \"row_index\": 11, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1532.9482555389404, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 37, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Collateral\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:49.858188Z\", \"row_index\": 12, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1665.6053066253662, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 37, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Contact\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates strongly indicate different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:50.958746Z\", \"row_index\": 13, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1097.5582599639893, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 45, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Contact\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates indicate likely different entities; no corroborating data to link them.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:52.745230Z\", \"row_index\": 14, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1782.485008239746, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 42, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cocoon\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no evidence they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:54.316204Z\", \"row_index\": 15, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1566.974401473999, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 52, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Country\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (1984-01-01 vs 1930-01-01).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:55.664459Z\", \"row_index\": 16, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1344.266414642334, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 41, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Confidence\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no overlapping identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:57.420809Z\", \"row_index\": 17, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1753.347635269165, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cowboy\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates; no evident overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:58.644269Z\", \"row_index\": 18, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1219.2182540893555, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cowboy\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; Cowboy (1958) and Coquette (1930) appear to be distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:42:59.655374Z\", \"row_index\": 19, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1008.1028938293457, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Conquest\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates; no basis to link to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:00.736243Z\", \"row_index\": 20, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1076.869249343872, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1928-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.41, \\\"explanation\\\": \\\"Same title but different dates (1928 vs 1930) suggest different works or editions; lacking additional identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:02.876901Z\", \"row_index\": 21, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2137.0162963867188, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 51, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Milk\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates refer to different items; 'Milk' vs 'Misery' are distinct works and dates differ.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:03.912907Z\", \"row_index\": 22, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1033.005952835083, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different date; could be different editions or a different work. Insufficient evidence to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:05.321989Z\", \"row_index\": 23, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1406.0814380645752, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 42, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Missing\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:06.776910Z\", \"row_index\": 24, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1451.9217014312744, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Changeling\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no clear alias or cross-reference.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:08.345508Z\", \"row_index\": 25, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1563.5981559753418, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 42, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chicago\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities; no corroborating overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:09.390886Z\", \"row_index\": 26, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1042.3784255981445, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 42, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chocolat\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and very different dates; records likely refer to distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:10.935714Z\", \"row_index\": 27, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1540.9045219421387, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 40, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Character\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different title and date suggest different works; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:12.094435Z\", \"row_index\": 28, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1155.7211875915527, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chaplin\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works (Chaplin vs Charly).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:16.521887Z\", \"row_index\": 29, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 4424.452543258667, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charade\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different titles and dates suggest different works (Charade vs Charly; 1984 vs 1969).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:17.911628Z\", \"row_index\": 30, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1385.7405185699463, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chinatown\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates; no clear linkage between 'Chinatown' (1974) and 'Charly' (1969).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:19.975644Z\", \"row_index\": 31, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2060.0149631500244, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles are identical; dates differ by one year, which could be edition or release variant of the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:21.089221Z\", \"row_index\": 32, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1109.5762252807617, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 53, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chagall\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ ('Chagall' vs 'Charly') and dates are different; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:22.659199Z\", \"row_index\": 33, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1565.97900390625, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charade\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.26, \\\"explanation\\\": \\\"Different titles and distinct years suggest unrelated works (Charade is 1963, Charly is 1969).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:24.288572Z\", \"row_index\": 34, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1626.3718605041504, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 55, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Champion\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"The titles and dates are markedly different (Champion vs Charly; 1949 vs 1969), suggesting they describe distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:25.612683Z\", \"row_index\": 35, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1321.1088180541992, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 44, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Conscience of Nhem En\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different works; no indication they describe the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:27.505027Z\", \"row_index\": 36, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1887.341022491455, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 215, \"output_tokens\": 44, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Collector of Bedford Street\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are different; no clear indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:29.902064Z\", \"row_index\": 37, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2394.0374851226807, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 223, \"output_tokens\": 73, \"total_tokens\": 296, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Colours of My Father: A Portrait of Sam Borenstein\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are different; the left refers to a portrait of Sam Borenstein (likely a film/documentary about a painter) while the right is a different film 'The Color of Money' with a different year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:31.946009Z\", \"row_index\": 38, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2039.9470329284668, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 59, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Identical title with only a one-year date discrepancy; likely the same work (The Color of Money, film/book) where dates may differ across sources.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:33.653819Z\", \"row_index\": 39, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1703.810453414917, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 41, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Court-Martial of Billy Mitchell\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works; no evidence of identity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:34.927302Z\", \"row_index\": 40, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1269.4816589355469, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 215, \"output_tokens\": 50, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Conquest of Everest\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ substantially; unlikely same entity (a 1953 Everest conquest vs 1987 film).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:36.089686Z\", \"row_index\": 41, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1158.3869457244873, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pig\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:37.263771Z\", \"row_index\": 42, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1171.0858345031738, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 52, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pig\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly ('The Pig' vs 'The Pianist'); dates are also different, making same-entity unlikely.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:38.909565Z\", \"row_index\": 43, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1641.793966293335, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 50, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ ('The Pianist' vs 'The Piano') and release years are different; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:40.154931Z\", \"row_index\": 44, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1242.3198223114014, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Titles are identical but appear to refer to different release years (2002 vs 2003), suggesting different entities or versions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:41.534537Z\", \"row_index\": 45, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1375.6141662597656, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Same title but different dates suggest different items; 1993 vs 1994 likely different works or release years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:43.647837Z\", \"row_index\": 46, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2109.300136566162, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 51, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Titles differ ('The Piano' vs 'The Pianist') and dates are a decade apart, indicating different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:45.230284Z\", \"row_index\": 47, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1578.4461498260498, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 60, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pirate\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates do not align to the same work; 'The Pirate' (1948) vs 'The Piano' (1994) are different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:47.560614Z\", \"row_index\": 48, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2326.329469680786, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 54, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pirate\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates are clearly different (The Pirate vs The Pianist; 1948 vs 2003), indicating different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:48.519582Z\", \"row_index\": 49, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 955.9683799743652, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 41, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Happy-Go-Lucky\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:50.398449Z\", \"row_index\": 50, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1875.8642673492432, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hardwood\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates differ significantly; 'Hardwood' (2004) unlikely to be Hamlet (1949).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:51.665073Z\", \"row_index\": 51, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1263.624906539917, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Same title but different dates; unlikely same work given distinct years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:52.680663Z\", \"row_index\": 52, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1011.5909576416016, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Same title but different dates; likely different works or productions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:53.940369Z\", \"row_index\": 53, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1256.706953048706, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Havana\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works and times (Havana vs Hamlet; 1990 vs 1949) suggesting different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:55.805709Z\", \"row_index\": 54, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1862.3371124267578, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 47, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hanussen\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works (Hanussen vs Hamlet) with no strong matching attributes.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:57.449293Z\", \"row_index\": 55, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1640.5842304229736, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 40, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harvest\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and no overlapping data to suggest a single work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:43:59.185326Z\", \"row_index\": 56, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1733.0331802368164, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hawaii\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different works and time periods; no evident overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:00.465148Z\", \"row_index\": 57, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1275.8216857910156, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hatari!\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates indicate distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:01.816380Z\", \"row_index\": 58, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1347.2309112548828, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harvey\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ (Harvey vs Hamlet) and dates are close but specify different works; unlikely the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:03.665278Z\", \"row_index\": 59, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1845.8974361419678, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 49, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match and dates are close; minor date discrepancy but could refer to same work in different release years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:05.785651Z\", \"row_index\": 60, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2116.374731063843, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 56, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ratatouille\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different films; Ratatouille (2007) vs Ray (2004/2005) are distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:07.179186Z\", \"row_index\": 61, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1390.535593032837, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 55, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be versioning or release date variance, not enough to rule out same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:08.570298Z\", \"row_index\": 62, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1388.1113529205322, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 42, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ran\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles (Ran vs Ray) and different dates suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:09.948750Z\", \"row_index\": 63, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1374.4518756866455, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ragtime\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates suggest different works or entities (Ragtime vs Ray; 1981 vs 2005).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:11.358160Z\", \"row_index\": 64, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1405.4114818572998, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 57, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raoni\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities; no clear link between 'Raoni' (1978) and 'Ray' (2005).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:12.925053Z\", \"row_index\": 65, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1562.9024505615234, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 62, \"total_tokens\": 272, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Rashomon\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works; 'Rashomon' (1950s film) vs 'Ray' (2000s work) have no matching identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:14.188394Z\", \"row_index\": 66, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1259.3414783477783, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 40, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raffles\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and vastly different dates; no overlapping identifying information.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:15.536137Z\", \"row_index\": 67, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1344.7425365447998, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 58, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beaufort\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works (Beaufort vs Ben-Hur; 2007 vs 1960), unlikely to be same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:16.876919Z\", \"row_index\": 68, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1337.782859802246, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 38, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beloved\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:18.223711Z\", \"row_index\": 69, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1342.8030014038086, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 44, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beaches\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different works and years; no overlap suggests different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:19.679559Z\", \"row_index\": 70, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1452.847957611084, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 40, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beetlejuice\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different films with no plausible overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:21.007821Z\", \"row_index\": 71, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1324.260950088501, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 38, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Betrayal\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and vastly different dates indicate unrelated entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:22.351241Z\", \"row_index\": 72, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1339.4196033477783, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 44, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Benji\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates indicate different entities (Benji vs Ben-Hur).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:24.646889Z\", \"row_index\": 73, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2291.649103164673, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ben\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping dates strongly indicate different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:26.703998Z\", \"row_index\": 74, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2053.109884262085, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 42, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Becket\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and different years; unlikely to refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:28.326215Z\", \"row_index\": 75, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1618.2174682617188, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 59, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Both have the same title but different release years (1959 vs 1960); could be different editions or films. Insufficient certainty for a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:30.114635Z\", \"row_index\": 76, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1784.4200134277344, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 53, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Benjy\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly (Benjy vs Ben-Hur; 1951 vs 1960) suggesting different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:31.417686Z\", \"row_index\": 77, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1300.046682357788, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 43, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mongol\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works; no overlapping identifiers suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:32.647626Z\", \"row_index\": 78, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1226.9401550292969, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mongol\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no plausible overlap to indicate the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:33.659727Z\", \"row_index\": 79, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1008.101224899292, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 39, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:35.134051Z\", \"row_index\": 80, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1470.3238010406494, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 46, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Different release year (2003 vs 2004) suggest different entities although same title.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:36.655176Z\", \"row_index\": 81, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1518.1248188018799, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"More\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; unlikely they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:37.891495Z\", \"row_index\": 82, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1233.3171367645264, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 37, \"total_tokens\": 245, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"More\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:39.128643Z\", \"row_index\": 83, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1233.1490516662598, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 72, \"total_tokens\": 284, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Both records share the same title 'Moonstruck', with only the date differing by year (1987 vs 1988); this could reflect a release year discrepancy but the core entity appears to be the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:40.409594Z\", \"row_index\": 84, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1277.9524326324463, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and years; no clear indication they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:41.630557Z\", \"row_index\": 85, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1217.963695526123, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonraker\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles (Moonraker vs Moonstruck) and different dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:42.930209Z\", \"row_index\": 86, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1295.6523895263672, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonraker\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates differ significantly; Moonraker (1979) vs Monster (2004) refer to different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:44.701155Z\", \"row_index\": 87, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1766.9453620910645, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morgan!\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates indicate different works; no strong or contextual overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:45.794854Z\", \"row_index\": 88, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1089.6995067596436, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 38, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morgan!\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works/entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:47.127858Z\", \"row_index\": 89, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1330.0049304962158, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 56, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morituri\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and different dates strongly suggest they are not the same work (Morituri 1965 vs Moonstruck 1988).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:48.274755Z\", \"row_index\": 90, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1142.895221710205, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morituri\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no overlapping identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:51.932891Z\", \"row_index\": 91, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 3655.1353931427, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 49, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonbird\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.19, \\\"explanation\\\": \\\"Titles differ significantly (Moonbird vs Moonstruck) and dates are decades apart, suggesting different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:53.918488Z\", \"row_index\": 92, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1982.5942516326904, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 37, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonbird\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:55.074894Z\", \"row_index\": 93, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1152.405023574829, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mogambo\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates indicate distinct works; no sufficient overlap to link records to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:56.244502Z\", \"row_index\": 94, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1165.0021076202393, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 39, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mogambo\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; unlikely same film or entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:57.489962Z\", \"row_index\": 95, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1242.4592971801758, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 48, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonrise\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles differ (Moonrise vs Moonstruck) and dates are decades apart, unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:44:58.776961Z\", \"row_index\": 96, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1283.9975357055664, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 53, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonrise\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; Moonrise (1948) vs Monster (2004) appear to refer to different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:00.602816Z\", \"row_index\": 97, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1821.850061416626, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moontide\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly ('Moontide' vs 'Moonstruck') and dates are decades apart, suggesting different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:02.444965Z\", \"row_index\": 98, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1839.1497135162354, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 45, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moontide\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and vastly different dates; no sufficient overlap to link to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:04.097754Z\", \"row_index\": 99, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1648.7882137298584, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 52, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morocco\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates are unrelated; Morocco (1930) vs Moonstruck (1988) refer to different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:05.620094Z\", \"row_index\": 100, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1519.338607788086, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 47, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morocco\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\":false,\\\"score\\\":0.12,\\\"explanation\\\":\\\"The titles differ greatly ('Morocco' vs 'Monster') and the dates are far apart, indicating different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:08.325993Z\", \"row_index\": 101, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2701.899290084839, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 44, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cars\\\", \\\"date\\\": \\\"2006-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different works; no overlapping attributes suggesting a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:09.641374Z\", \"row_index\": 102, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1311.38014793396, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Capote\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ significantly; Capote (2005) and Cabaret (1973) are distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:11.029645Z\", \"row_index\": 103, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1385.2696418762207, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cashback\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates are markedly different; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:12.203322Z\", \"row_index\": 104, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1169.6770191192627, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caravan\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:13.344264Z\", \"row_index\": 105, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1136.9431018829346, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 47, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Canhead\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates suggest different works; no overlap in identifiers aligning to same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:15.053980Z\", \"row_index\": 106, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1705.7173252105713, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 43, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casino\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates; no basis to link them as same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:16.104036Z\", \"row_index\": 107, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1046.055793762207, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camila\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (Camila vs Cabaret; 1984 vs 1973).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:17.279496Z\", \"row_index\": 108, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1171.4584827423096, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carmen\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no evident overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:18.745725Z\", \"row_index\": 109, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1463.238000869751, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 59, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caravans\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly ('Caravans' vs 'Cabaret') and dates (1978 vs 1973) do not align; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:20.409565Z\", \"row_index\": 110, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1659.8403453826904, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carrie\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and years suggest they refer to different works (Carrie vs Cabaret; 1976 vs 1973).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:21.687982Z\", \"row_index\": 111, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1274.416446685791, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 49, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.41, \\\"explanation\\\": \\\"Same title but different year in date; could be different productions or years; insufficient to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:23.168421Z\", \"row_index\": 112, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1476.438045501709, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camelot\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no plausible overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:24.786377Z\", \"row_index\": 113, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1613.9566898345947, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 56, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Can-Can\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; 'Can-Can' (1960) vs 'Cabaret' (1973) refer to distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:26.167709Z\", \"row_index\": 114, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1377.3319721221924, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 37, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Career\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates indicate distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:33.250824Z\", \"row_index\": 115, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 7080.112934112549, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carrie\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works (Carrie vs Cabaret) with no matching attributes to indicate same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:34.640407Z\", \"row_index\": 116, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1385.582685470581, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 56, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caged\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates describe different works (Caged vs Cabaret; 1950 vs 1973), unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:36.044231Z\", \"row_index\": 117, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1400.8243083953857, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casbah\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ significantly; likely referring to different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:37.364069Z\", \"row_index\": 118, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1315.8385753631592, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casablanca\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to distinct films (Casablanca 1943 vs Cabaret 1973); no alignment in attributes.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:38.447996Z\", \"row_index\": 119, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1080.9266567230225, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carefree\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates differ substantially; no evidence they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:40.209954Z\", \"row_index\": 120, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1758.9585781097412, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 48, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camille\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities; no evidence of aliasing or related work linking them.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:41.768744Z\", \"row_index\": 121, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1554.7897815704346, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 45, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cavalcade\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no evidence of aliasing or relation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:43.204047Z\", \"row_index\": 122, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1432.3022365570068, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maestro\\\", \\\"date\\\": \\\"2006-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates are different (Maestro vs Marty; 2006 vs 1956), no strong overlap to indicate same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:44.746932Z\", \"row_index\": 123, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1538.8853549957275, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 40, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mal\\ufffdna\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no clear overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:45.745798Z\", \"row_index\": 124, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 994.8654174804688, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Magnolia\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:47.298652Z\", \"row_index\": 125, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1548.8522052764893, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mandela\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates clearly indicate different entities; no evident overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:48.860888Z\", \"row_index\": 126, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1559.237003326416, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 55, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maverick\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ significantly (Maverick 1994 vs Marty 1956) with no clear overlap; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:50.137292Z\", \"row_index\": 127, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1273.4034061431885, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 46, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manipulation\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Differences in title and date strongly suggest different entities; nothing in common indicates a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:51.754202Z\", \"row_index\": 128, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1612.910509109497, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Matewan\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates indicate distinct entities; no overlapping identifiers to suggest a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:53.486547Z\", \"row_index\": 129, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1729.3448448181152, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maurice\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates suggest different individuals; no overlap in identifying fields.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:54.976741Z\", \"row_index\": 130, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1487.1931076049805, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 38, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mannequin\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and different dates strongly suggest separate entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:56.646904Z\", \"row_index\": 131, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1666.1643981933594, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 41, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mask\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are different; no overlapping identifiers suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:58.044640Z\", \"row_index\": 132, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1393.7361240386963, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 41, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marlene\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different individuals; no overlapping attributes.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:45:59.224822Z\", \"row_index\": 133, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1176.1817932128906, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manhattan\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities; no clear overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:00.682560Z\", \"row_index\": 134, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1454.7367095947266, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mahogany\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (Mahogany vs Marty; 1975 vs 1956).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:02.377438Z\", \"row_index\": 135, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1691.8792724609375, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manson\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates suggest different entities; no strong overlap in identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:03.487755Z\", \"row_index\": 136, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1106.3191890716553, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marjoe\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates; insufficient similarity to indicate the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:05.462406Z\", \"row_index\": 137, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1971.651554107666, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Madron\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no clear overlap to indicate same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:07.429732Z\", \"row_index\": 138, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1964.325189590454, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 42, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marooned\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no corroborating identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:08.698309Z\", \"row_index\": 139, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1265.5766010284424, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 39, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mandragola\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:09.897794Z\", \"row_index\": 140, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1195.4841613769531, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 38, \"total_tokens\": 248, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Macario\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works/entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:11.258314Z\", \"row_index\": 141, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1356.5208911895752, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 60, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Both records share the same title 'Marty' but have different dates; the similarity is plausible for the same entity with a different year, though uncertainty remains.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:17.512148Z\", \"row_index\": 142, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 6249.833106994629, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Madeline\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Different titles and different dates; no strong evidence they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:18.938358Z\", \"row_index\": 143, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1423.2099056243896, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marie-Louise\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different individuals; 'Marie-Louise' vs 'Marty' likely distinct persons.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:20.350237Z\", \"row_index\": 144, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1408.8795185089111, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 41, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mannequin\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates; there is no indication of shared identity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:22.203762Z\", \"row_index\": 145, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1849.5244979858398, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maytime\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:23.890941Z\", \"row_index\": 146, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1683.1796169281006, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 43, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Match Point\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to completely different works; no overlap indicating same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:25.348323Z\", \"row_index\": 147, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1454.3836116790771, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 63, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates are close but differ by one year, which may reflect different release years or editions; overall, high likelihood they refer to the same Mary Poppins.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:27.287476Z\", \"row_index\": 148, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1936.1493587493896, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 50, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Million Dollar Baby\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Million Dollar Baby\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.8, \\\"explanation\\\": \\\"Same title with different date; likely same film with release-year discrepancy or different release date in a different region.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:29.457943Z\", \"row_index\": 149, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2166.476249694824, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 40, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Incredibles\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and release years; unlikely to be same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:30.945717Z\", \"row_index\": 150, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1483.773946762085, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 41, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Insider\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no clear overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:32.588970Z\", \"row_index\": 151, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1640.2547359466553, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 45, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Invaders\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates imply different works; low likelihood of being the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:33.875394Z\", \"row_index\": 152, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1283.4241390228271, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 40, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different year; potential different works or editions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:35.410883Z\", \"row_index\": 153, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1532.4897766113281, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 44, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of the Weeping Camel\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to different works with different dates; unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:36.447726Z\", \"row_index\": 154, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1032.8431129455566, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 57, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Statue of Liberty\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different subjects (Statue of Liberty vs. Louis Pasteur story) and there is no overlap suggesting a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:38.026305Z\", \"row_index\": 155, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1574.5813846588135, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 45, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Adele H.\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works/persons; unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:39.829593Z\", \"row_index\": 156, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1800.2874851226807, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 60, \"total_tokens\": 277, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Three Loves\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles and dates refer to different works/persons (The Story of Three Loves vs The Story of Louis Pasteur) and do not align as the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:41.141581Z\", \"row_index\": 157, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1307.9884052276611, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 44, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Time\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; unlikely same work or author; weak or no overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:42.620730Z\", \"row_index\": 158, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1475.149154663086, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 40, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Dr. Wassell\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates indicate distinct works likely about different subjects.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:43.536699Z\", \"row_index\": 159, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 911.9677543640137, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 46, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Identical title with only one-year date difference; likely same work with publication year variation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:45.062411Z\", \"row_index\": 160, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1521.712303161621, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 58, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mystic River\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mystic River\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; years differ by one year which could be release date variation; other fields identical (if only these fields exist, assume same film).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:46.280453Z\", \"row_index\": 161, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1215.0423526763916, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be alternate edition or release date; insufficient to deem different.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:47.956750Z\", \"row_index\": 162, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1672.2958087921143, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hospital\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates; no indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:49.542765Z\", \"row_index\": 163, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1583.0156803131104, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 56, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hole\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; 'The Hole' (1962) vs 'The Hours' (2003) refer to different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:51.202109Z\", \"row_index\": 164, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1656.3441753387451, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 45, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hoaxters\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; no clear overlap in entity attributes to indicate same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:52.494759Z\", \"row_index\": 165, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1289.6509170532227, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 59, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The ChubbChubbs!\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; no plausible link between 'The ChubbChubbs!' (2002) and 'The Champ' (1933).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:53.826825Z\", \"row_index\": 166, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1328.064203262329, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 44, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Childeater\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; no clear indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:55.661463Z\", \"row_index\": 167, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1831.6380977630615, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.38, \\\"explanation\\\": \\\"Same title but different dates suggest different works; potential ambiguity cannot confirm overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:57.879344Z\", \"row_index\": 168, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2214.8807048797607, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 43, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Thursday's Children\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates; no evidence suggesting they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:46:59.147887Z\", \"row_index\": 169, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1264.5435333251953, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Thousands Cheer\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates; no strong link indicating same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:00.353837Z\", \"row_index\": 170, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1202.9502391815186, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title but different date; could refer to remakes or releases with same name. Score reflects probable same entity with variations.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:01.551423Z\", \"row_index\": 171, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1193.5853958129883, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Training Day\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Training Day\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.9, \\\"explanation\\\": \\\"Titles and dates identical; high confidence they refer to the same entity (Training Day, 2001-01-01).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:03.219341Z\", \"row_index\": 172, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1664.9203300476074, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 69, \"total_tokens\": 281, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster's Ball\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monsters Ball\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Titles are highly similar but not identical ('Monster's Ball' vs 'Monsters Ball') and dates differ by year; could be different works or a variant spelling. Insufficient evidence to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:05.024869Z\", \"row_index\": 173, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1801.5308380126953, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shrek\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:06.376125Z\", \"row_index\": 174, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1347.2559452056885, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.44, \\\"explanation\\\": \\\"Same title but different year; without additional identifiers, the 1996 vs 1997 date suggests different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:07.896254Z\", \"row_index\": 175, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1516.1311626434326, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shadowlands\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:09.575620Z\", \"row_index\": 176, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1676.3627529144287, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 49, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shoeshine\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Titles differ significantly (Shoeshine vs Shine) and dates are a decade apart, suggesting different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:10.745877Z\", \"row_index\": 177, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1166.2564277648926, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shampoo\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates imply different works; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:12.451212Z\", \"row_index\": 178, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1701.3418674468994, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shanks\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no strong overlap to indicate same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:13.944924Z\", \"row_index\": 179, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1490.7128810882568, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shaft\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no matching attributes to link them.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:15.379679Z\", \"row_index\": 180, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1431.7543506622314, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 40, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shenandoah\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates suggest different entities; no strong overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:17.053357Z\", \"row_index\": 181, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1669.677972793579, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shane\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles (Shane vs Shine) and vastly different dates imply different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:18.539923Z\", \"row_index\": 182, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1482.5615882873535, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 63, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shoe-Shine\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Titles 'Shoe-Shine' vs 'Shine' and dates 1947 vs 1997 strongly suggest different works or editions; insufficient overlap to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:20.054364Z\", \"row_index\": 183, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1511.4409923553467, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 51, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Am\\ufffdlie\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly (Am\\u00e9lie vs Amadeus) and dates refer to different works; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:21.282855Z\", \"row_index\": 184, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1224.4904041290283, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 37, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amistad\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.13, \\\"explanation\\\": \\\"Different titles and release years indicate distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:22.310859Z\", \"row_index\": 185, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1025.0036716461182, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 39, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amazon\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no overlap suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:24.027674Z\", \"row_index\": 186, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1712.8150463104248, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Both records share the same title; date differs by one year which may reflect edition/year or data inconsistency, but likely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:25.310065Z\", \"row_index\": 187, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1279.3900966644287, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 54, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amarcord\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ significantly (Amarcord vs Amadeus; 1975 vs 1985), unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:27.717021Z\", \"row_index\": 188, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2403.9559364318848, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 45, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amarcord\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and different release years; no strong evidence they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:30.311955Z\", \"row_index\": 189, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2591.933012008667, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 39, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"the accountant\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; unlikely same work or entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:31.898672Z\", \"row_index\": 190, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1583.0423831939697, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 58, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title with different year; could be sequel/remake but insufficient to distinguish; modest confidence they refer to similar work; treated as potential same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:33.498662Z\", \"row_index\": 191, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1596.9915390014648, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 42, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Actress\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates suggest distinct works; no overlap in identifying details.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:34.731665Z\", \"row_index\": 192, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1230.0009727478027, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 58, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title 'Gladiator' with close release year; dates differ by one year which may reflect data quality or edition; likely the same movie.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:36.667113Z\", \"row_index\": 193, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1932.4524402618408, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 56, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Glory\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates differ substantially; 'Glory' (1989) vs 'Gladiator' (2001) suggest different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:37.658950Z\", \"row_index\": 194, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 987.8373146057129, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 56, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gloria\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates differ substantially; unlikely the same entity (1980 film 'Gloria' vs 2001 film 'Gladiator').\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:39.351054Z\", \"row_index\": 195, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1688.1048679351807, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Glass\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are clearly different (Glass vs Gladiator; 1959 vs 2001); no close match indicates distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:41.070090Z\", \"row_index\": 196, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1716.0365581512451, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 53, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Erin Brockovich\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Erin Brockovich\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year likely due to edition/publication year discrepancy; overall high likelihood of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:42.653793Z\", \"row_index\": 197, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1580.7039737701416, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"American Beauty\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"American Beauty\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different release year (1999 vs 2000) likely indicates different works or editions; uncertainty but not strong match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:44.892364Z\", \"row_index\": 198, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2234.571695327759, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 53, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boys Don't Cry\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Don't Cry\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title with close release year; date discrepancy but could be re-release or edition. Overall sufficient similarity to consider same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:46.214247Z\", \"row_index\": 199, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1317.8832530975342, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Humdrum\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.14, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no sufficient overlap to match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:47.714908Z\", \"row_index\": 200, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1496.6628551483154, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 52, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hungarians\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.19, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works or entities (Hungarians vs Hud; 1978 vs 1964).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:49.291480Z\", \"row_index\": 201, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1572.5724697113037, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 41, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hunger\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles and different dates; no strong evidence of same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:51.027736Z\", \"row_index\": 202, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1732.2533130645752, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 59, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but dates differ by year; could be the same work with different release dates, but the 1963 vs 1964 discrepancy reduces confidence.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:52.292464Z\", \"row_index\": 203, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1261.728048324585, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 49, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Humoresque\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works (Humoresque 1946 vs Hud 1964).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:54.188758Z\", \"row_index\": 204, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1892.2948837280273, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 59, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Life Is Beautiful\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Life is Beautiful\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles are the same apart from capitalization; dates differ by one year which could reflect release year variants or data inconsistency, suggesting high but not certain match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:55.629709Z\", \"row_index\": 205, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1437.9510879516602, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 44, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shakespeare in Love\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shakespeare in Love\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title; differing year could be release year inconsistencies; overall high similarity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:57.466841Z\", \"row_index\": 206, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1833.1310749053955, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 59, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dancemaker\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates do not align; 'Dancemaker' (1998) vs 'Dangerous' (1936) appear to be different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:47:59.009477Z\", \"row_index\": 207, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1538.640022277832, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 37, \"total_tokens\": 248, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dancemaker\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates indicate distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:00.386983Z\", \"row_index\": 208, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1373.504400253296, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daylight\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates indicate different entities; no overlap suggesting same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:02.597080Z\", \"row_index\": 209, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2206.0959339141846, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daylight\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no overlapping attributes suggest distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:03.934302Z\", \"row_index\": 210, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1334.2201709747314, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 53, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dave\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles and dates; no evident link between 'Dave' (1993) and 'Dangerous' (1936).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:05.640357Z\", \"row_index\": 211, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1702.0554542541504, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 44, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dave\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates suggest different entities; no overlaps to indicate a single individual.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:07.332767Z\", \"row_index\": 212, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1689.408540725708, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 55, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Damage\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and vastly different dates; no strong link between 'Damage' (1992) and 'Dangerous' (1936).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:09.218771Z\", \"row_index\": 213, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1883.0044269561768, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 42, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Damage\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities; no overlapping identifying information.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:11.143864Z\", \"row_index\": 214, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1921.0920333862305, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 57, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daens\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are clearly different (Daens vs Dangerous; 1992 vs 1936); no indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:13.237982Z\", \"row_index\": 215, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2091.1192893981934, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 38, \"total_tokens\": 248, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daens\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:15.213160Z\", \"row_index\": 216, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1972.1746444702148, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 40, \"total_tokens\": 249, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dad\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates; no clear linkage suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:17.020600Z\", \"row_index\": 217, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1803.7900924682617, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 38, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dad\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and unrelated dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:18.690890Z\", \"row_index\": 218, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1667.2899723052979, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 62, \"total_tokens\": 272, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"The titles 'Dae' and 'Dangerous' and dates '1979' vs '1936' are markedly different; unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:20.283229Z\", \"row_index\": 219, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1588.3371829986572, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 42, \"total_tokens\": 252, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates make it unlikely they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:21.814040Z\", \"row_index\": 220, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1527.8115272521973, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no overlapping attributes suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:23.994670Z\", \"row_index\": 221, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2176.6340732574463, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 54, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.38, \\\"explanation\\\": \\\"Same title but different release year (1965 vs 1966) suggests different works or editions; insufficient to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:25.431694Z\", \"row_index\": 222, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1433.0227375030518, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Different dates (1935 vs 1936) suggest they are not the same work; title alone is insufficient to confirm a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:26.553772Z\", \"row_index\": 223, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1119.0776824951172, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:27.773755Z\", \"row_index\": 224, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1215.982437133789, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 40, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prince of Egypt\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates; unlikely same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:29.015799Z\", \"row_index\": 225, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1238.044023513794, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 55, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prince of Tides\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works (The Prince of Tides vs The Prime of Miss Jean Brodie) with no evident overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:30.961272Z\", \"row_index\": 226, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1942.4729347229004, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 43, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Profession of Arms\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates; no indication they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:32.381959Z\", \"row_index\": 227, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1417.6867008209229, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 220, \"output_tokens\": 53, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Titles match but dates differ by year; could be different editions or a film vs. book. Unclear without additional identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:33.468440Z\", \"row_index\": 228, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1082.4813842773438, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 39, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pride of St. Louis\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates are clearly different; unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:35.565526Z\", \"row_index\": 229, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2094.085216522217, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 46, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pride of the Yankees\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles refer to different works with distinct release dates; low likelihood of being the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:36.763778Z\", \"row_index\": 230, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1195.2528953552246, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 40, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Price of Victory\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely same work or person.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:38.145562Z\", \"row_index\": 231, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1378.7827491760254, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 44, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prisoner of Zenda\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates indicate distinct works; unlikely the same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:39.540591Z\", \"row_index\": 232, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1392.0292854309082, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 61, \"total_tokens\": 277, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"As Good as It Gets\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"As Good As It Gets\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Titles are the same except for capitalization; dates differ by year (1997 vs 1998), suggesting different releases. Without additional context, not a definite match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:40.912895Z\", \"row_index\": 233, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1369.3029880523682, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates (1997 vs 1957) suggest different works or entities; insufficient overlap to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:43.043393Z\", \"row_index\": 234, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2126.4970302581787, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 50, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anna\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different individuals (Anna vs Anastasia; 1987 vs 1957).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:44.540841Z\", \"row_index\": 235, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1493.4487342834473, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 52, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Annie\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly (Annie vs Anastasia; 1982 vs 1957) suggesting different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:45.793431Z\", \"row_index\": 236, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1248.5933303833008, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates (1956 vs 1957) may indicate different works or editions; insufficient to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:47.017489Z\", \"row_index\": 237, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1220.060110092163, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 46, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Face/Off\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles; both dated 1997-01-01 but refer to different films.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:48.318852Z\", \"row_index\": 238, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1297.372579574585, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Both records have the same title but different dates (1996 vs 1997), suggesting they are not the same release/edition.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:49.744117Z\", \"row_index\": 239, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1422.2652912139893, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 54, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fame\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly (Fame vs Fargo; 1980 vs 1997), unlikely to refer to same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:51.080677Z\", \"row_index\": 240, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1333.559513092041, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 37, \"total_tokens\": 246, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Faces\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and years strongly suggest separate entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:52.211293Z\", \"row_index\": 241, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1127.6178359985352, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 54, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fanny\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no plausible link between 'Fanny' (1961) and 'Fargo' (1997).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:53.579391Z\", \"row_index\": 242, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1364.0978336334229, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 49, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Leaving Las Vegas\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Leaving Las Vegas\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which may reflect release year discrepancies, but likely same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:54.673974Z\", \"row_index\": 243, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1091.5820598602295, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dead Man Walking\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dead Man Walking\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles identical; dates differ by one year which could be release vs. production date; likely same work with inconsistent date data.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:55.614036Z\", \"row_index\": 244, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 937.0617866516113, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 54, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Forrest Gump\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Forest Gump\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.41, \\\"explanation\\\": \\\"Titles differ by one letter ('Forrest' vs 'Forest') and dates differ by year, suggesting they refer to different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:57.004616Z\", \"row_index\": 245, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1386.580467224121, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 51, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Nell\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works (Nell vs Network) with no corroborating details; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:48:58.515149Z\", \"row_index\": 246, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1506.5321922302246, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 55, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title 'Network' with near-identical dates; minor year difference could reflect edition or data variance, supporting a likely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:00.044827Z\", \"row_index\": 247, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1526.6766548156738, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 43, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Neighbours\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates; no indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:01.378924Z\", \"row_index\": 248, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1330.09934425354, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Identical titles but different dates suggest different entities (e.g., release year changes); insufficient correlation to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:02.953051Z\", \"row_index\": 249, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1570.124626159668, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 61, \"total_tokens\": 272, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Blue Skies\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are very similar but differ ('Blue Skies' vs 'Blue Sky') and dates are far apart (1946 vs 1995), suggesting different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:04.398939Z\", \"row_index\": 250, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1441.887378692627, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 208, \"output_tokens\": 54, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different date (1993 vs 1994) suggests different entities or editions; insufficient evidence they are the same.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:05.633133Z\", \"row_index\": 251, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1230.1945686340332, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 44, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pharaoh\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates are clearly different; no evidence they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:06.940282Z\", \"row_index\": 252, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1304.1481971740723, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Phaedra\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly (Phaedra vs Philadelphia; 1962 vs 1994), unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:08.401147Z\", \"row_index\": 253, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1457.8666687011719, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 50, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Partners\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (Partners vs Patton; 1993 vs 1971).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:09.853973Z\", \"row_index\": 254, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1449.8255252838135, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 47, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Parenthood\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (1989 Parenthood vs 1971 Patton).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:11.224472Z\", \"row_index\": 255, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1366.4987087249756, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pathfinder\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates strongly suggest they refer to different entities (Pathfinder vs Patton; 1987 vs 1971).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:13.204666Z\", \"row_index\": 256, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1976.1936664581299, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 37, \"total_tokens\": 247, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paradise\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and years strongly indicate different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:14.994521Z\", \"row_index\": 257, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1785.8550548553467, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Papillon\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different films (Papillon vs Patton) from different years; unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:16.520351Z\", \"row_index\": 258, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1521.8334197998047, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 65, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Both records share the same title 'Patton' and are close in date (1970 vs 1971), likely referring to the same work with a publication or release year variation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:17.625942Z\", \"row_index\": 259, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1102.5872230529785, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 54, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pan\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; 'Pan' vs 'Patton' and 1962 vs 1971 suggest different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:19.047967Z\", \"row_index\": 260, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1418.0359840393066, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paw\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely same work or entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:20.426048Z\", \"row_index\": 261, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1374.0801811218262, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paisan\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates are for different works (Paisan is 1949, Patton is 1971) with distinct subject matter.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:21.944761Z\", \"row_index\": 262, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1514.7125720977783, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 54, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paris--Underground\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works/persons (Paris--Underground vs Patton) and different years; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:23.936197Z\", \"row_index\": 263, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1987.4353408813477, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 52, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title; differing release year by one year may be due to release date differences or data error; likely same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:25.984106Z\", \"row_index\": 264, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2043.9045429229736, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 61, \"total_tokens\": 277, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Identical title; different dates could reflect different releases/remakes (1975 vs 1993) but likely same work with re-release or adaptation; moderate confidence.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:27.859474Z\", \"row_index\": 265, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1871.3760375976562, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Howards End\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Howards End\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be due to release year variations; high likelihood they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:30.154491Z\", \"row_index\": 266, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2291.0168170928955, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 47, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates correspond to distinct works released in different years; unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:31.600025Z\", \"row_index\": 267, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1441.545009613037, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 56, \"total_tokens\": 274, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Titles are identical; release year differs by one; likely same film with different date representation (original vs. re-release) indicating same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:33.365782Z\", \"row_index\": 268, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1761.756181716919, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 45, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sign of the Cross\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly and dates are one year apart; no strong relation suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:35.065431Z\", \"row_index\": 269, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1695.6508159637451, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 40, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sign of the Cross\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates refer to different works; no plausible overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:36.329012Z\", \"row_index\": 270, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1259.5820426940918, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 220, \"output_tokens\": 55, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are identical but dates differ by two years, suggesting different works or misrecording; uncertainty remains but likely different editions or releases.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:37.584000Z\", \"row_index\": 271, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1250.990629196167, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 38, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and vastly different dates indicate unrelated entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:38.711303Z\", \"row_index\": 272, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1123.3022212982178, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 40, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Same title but different dates; likely different works or productions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:40.011209Z\", \"row_index\": 273, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1295.9058284759521, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 61, \"total_tokens\": 279, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Both records share the same title; dates differ by one year, which could reflect different release years of the same work or data error, but strongly suggests the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:41.473549Z\", \"row_index\": 274, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1458.3399295806885, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 57, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Reversal of Fortune\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Reversal of Fortune\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; the dates differ by one year, which may be a data discrepancy or edition year; overall likelihood of same entity is plausible.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:42.654031Z\", \"row_index\": 275, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1177.4818897247314, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ghost\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ghandi\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no strong link suggesting same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:44.172703Z\", \"row_index\": 276, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1514.6708488464355, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 48, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ghostbusters\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ghandi\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates differ (Ghostbusters 1984 vs Gandhi 1983), indicating different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:45.272650Z\", \"row_index\": 277, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1095.947504043579, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 58, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"My Left Foot\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"My Left Foot\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year, which may reflect release vs. production dates; enough similarity to consider same work with potential date discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:46.563661Z\", \"row_index\": 278, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1288.0115509033203, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 57, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Driving Miss Daisy\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Driving Miss Daisy\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year, which could reflect release vs. release date differences or data inconsistency, but likely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:48.943377Z\", \"row_index\": 279, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2376.716136932373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 55, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Rain Man\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Rain Man\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Same title 'Rain Man' with only a one-year difference in date; could reflect release year discrepancies across sources, likely same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:50.536772Z\", \"row_index\": 280, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1588.3934497833252, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 45, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunset\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and radically different dates indicate they are unlikely to refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:51.892601Z\", \"row_index\": 281, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1351.8290519714355, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 43, \"total_tokens\": 253, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Superman\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different entities (preclude likely same item).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:53.812302Z\", \"row_index\": 282, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1916.7006015777588, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 40, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunflower\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely same work or entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:54.970002Z\", \"row_index\": 283, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1154.6993255615234, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Summertime\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different dates; unlikely to refer to same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:56.602011Z\", \"row_index\": 284, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1629.0078163146973, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 48, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but dates differ by a year; without additional identifiers they are likely different works or editions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:57.882783Z\", \"row_index\": 285, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1277.7724266052246, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 56, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sundown\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles and dates differ (Sundown vs Suspicion; 1941 vs 1942), indicating different works and likely different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:49:59.511572Z\", \"row_index\": 286, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1624.7899532318115, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 209, \"output_tokens\": 41, \"total_tokens\": 250, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunny\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different years; no overlapping identifiers suggest distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:00.656012Z\", \"row_index\": 287, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1141.4389610290527, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Superman\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and different years; no evidence of a shared entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:02.422358Z\", \"row_index\": 288, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1763.345718383789, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 41, \"total_tokens\": 251, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suez\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; unlikely to refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:03.677704Z\", \"row_index\": 289, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1252.3458003997803, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 46, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suzy\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works (Suzy vs Suspicion) with unrelated years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:04.835542Z\", \"row_index\": 290, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1154.8373699188232, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Identical title; dates differ by year, which could reflect a different release year or edition of the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:06.091244Z\", \"row_index\": 291, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1252.7034282684326, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 48, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Children of a Lesser God\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Children of a Lesser God\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but dates differ by one year; without other corroborating data, uncertain if same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:07.858528Z\", \"row_index\": 292, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1763.2966041564941, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 51, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Same title; differing date could be due to publication vs. production year; content appears to refer to same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:08.893188Z\", \"row_index\": 293, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1030.6601524353027, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 42, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"King of the Zombies\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates indicate distinct works; no overlap in key identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:10.392355Z\", \"row_index\": 294, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1494.1661357879639, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 60, \"total_tokens\": 276, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kings of the Turf\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and dates; no obvious link between 'Kings of the Turf' (1941) and 'Kiss of the Spider Woman' (1986).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:11.829729Z\", \"row_index\": 295, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1434.372901916504, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Angry Harvest\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles and dates refer to different works (Angry Harvest vs Annie Hall; 1985 vs 1978), unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:13.598079Z\", \"row_index\": 296, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1764.357566833496, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match; dates differ by one year which could be release vs production discrepancy, suggesting potential same film with release year ambiguity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:15.129555Z\", \"row_index\": 297, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1528.4864902496338, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 51, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Places in the Heart\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Places in the Heart\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Identical title with only a one-year date difference; likely the same work with a production/release year variance.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:16.243069Z\", \"row_index\": 298, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1110.513687133789, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 46, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Tender Mercies\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Tender Mercies\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.38, \\\"explanation\\\": \\\"Titles match but dates differ by a year; could be different releases or a data error.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:17.654191Z\", \"row_index\": 299, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1407.12308883667, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 48, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Terms of Endearment\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Terms of Endearment\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles match but the dates differ (1983 vs 1984), suggesting different editions or entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:19.274780Z\", \"row_index\": 300, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1616.589069366455, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 64, \"total_tokens\": 277, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sophie's Choice\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Sophie\\ufffds Choice\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles appear to refer to the same work, but dates differ by one year and contain a potential encoding issue (Sophie\\ufffds vs Sophie's). Ambiguity prevents definite match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:20.825507Z\", \"row_index\": 301, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1547.7256774902344, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 44, \"total_tokens\": 255, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Diner\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates refer to different works with no overlapping identifiers; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:22.094099Z\", \"row_index\": 302, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1264.592170715332, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 42, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dillinger\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates; no indication they refer to same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:23.950667Z\", \"row_index\": 303, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1853.5666465759277, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Same title but different dates suggest different works or editions; insufficient overlap to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:25.355713Z\", \"row_index\": 304, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1401.0462760925293, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 45, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"On Golden Pond\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"On Golden Pond\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Same title; differing year may be edition/release date but likely the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:26.825330Z\", \"row_index\": 305, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1465.6167030334473, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 57, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raging Bull\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Raging Bull\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be due to release date variations or data inconsistency, but strongly suggests the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:28.025061Z\", \"row_index\": 306, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1195.7321166992188, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 52, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coal Miner's Daughter\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coal Miner\\ufffds Daughter\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are very similar but differ in apostrophe/encoding and dates differ by year, suggesting potential different versions or releases.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:31.385635Z\", \"row_index\": 307, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 3357.572555541992, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 46, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kramer vs. Kramer\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kramer vs. Kramer\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Titles match exactly and dates are close; likely same work but different release date year precision.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:32.540747Z\", \"row_index\": 308, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1151.109218597412, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 60, \"total_tokens\": 272, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Norma Rae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Norma Rae\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Identical title with different dates; could refer to same film with a release year discrepancy or re-release. Given common entity ambiguity, still plausible the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:33.938993Z\", \"row_index\": 309, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1395.2441215515137, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coming Home\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coming Home\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.36, \\\"explanation\\\": \\\"Same title but different date (1978 vs 1979) likely different works or editions; insufficient overlap to confirm.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:35.679200Z\", \"row_index\": 310, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1737.2069358825684, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Goodbye Girl\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Goodbye Girl\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Titles match but dates differ by year; could be different releases or a mismatch in year data.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:36.817528Z\", \"row_index\": 311, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1135.3263854980469, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 226, \"output_tokens\": 56, \"total_tokens\": 282, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"One Flew over the Cuckoo's Nest\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"One Flew Over The Cuckoo's Nes\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are highly similar but not identical and dates differ by a year; this inconsistency suggests they may refer to different works or metadata errors.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:38.118604Z\", \"row_index\": 312, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1298.0761528015137, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 48, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harry and Tonto\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Harry and Tonto\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Identical title; differing year likely due to release date discrepancy or edition; context suggests same film. \\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:40.389907Z\", \"row_index\": 313, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2267.3046588897705, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 221, \"output_tokens\": 58, \"total_tokens\": 279, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Alice Doesn't Live Here Anymore\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Alice Doesn\\ufffdt live Here Anymor\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles are highly similar with a minor typographical difference in the second variant; dates differ by year but could reflect a release date discrepancy or reissue.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:41.770029Z\", \"row_index\": 314, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1376.1215209960938, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 57, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Save the Tiger\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Save the Tiger\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Identical title with close, but not identical, dates (1973 vs 1974); likely same work with different date metadata or edition.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:43.337743Z\", \"row_index\": 315, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1563.7147426605225, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 55, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Touch of Class\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Touch of Class\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year, which could be due to release vs production year; overall high likelihood of same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:44.578190Z\", \"row_index\": 316, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1237.4475002288818, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 51, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Robin Hood\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and dates; they refer to distinct films (Robin Hood 1973 vs Roman Holiday 1954).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:46.035881Z\", \"row_index\": 317, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1453.6914825439453, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 59, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same movie title with close release year; one-year difference could be due to release date formatting or dataset inconsistency, but core entity likely the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:47.404158Z\", \"row_index\": 318, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1364.2737865447998, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 54, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Robin Hoodlum\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and dates are clearly different (Robin Hoodlum vs Roman Holiday; 1948 vs 1954), indicating different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:48.698718Z\", \"row_index\": 319, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1291.5596961975098, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 49, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title, only the year differs by one; likely the same film with a different release date entry.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:50.177807Z\", \"row_index\": 320, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1475.0888347625732, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 213, \"output_tokens\": 41, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Go-Between\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and different dates; no indication of a shared entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:52.360266Z\", \"row_index\": 321, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2178.4582138061523, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 58, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Goddess\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles and dates refer to different works (The Goddess vs The Godfather; 1958 vs 1973), unlikely to be the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:54.709023Z\", \"row_index\": 322, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2345.757484436035, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The French Connection\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The French Connection\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Same title with only a one-year date difference; likely referring to the same film/entity with a possible release date variation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:56.204614Z\", \"row_index\": 323, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1491.5904998779297, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 44, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Klute\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Klute\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.3, \\\"explanation\\\": \\\"Titles match but dates differ by one year; could refer to different release years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:57.852030Z\", \"row_index\": 324, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1643.416404724121, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 62, \"total_tokens\": 274, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Women in Love\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Women In Love\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.68, \\\"explanation\\\": \\\"Titles are the same work with minor capitalization variation; dates differ by year, but could reflect edition or release vs. production date, not enough to refute a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:50:58.836247Z\", \"row_index\": 325, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 981.2166690826416, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 50, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Titles match exactly but dates differ; could refer to same work with different release dates or adaptations. Moderate confidence.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:00.848070Z\", \"row_index\": 326, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2008.8224411010742, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 57, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title but different release year; could refer to the same film with a different date source or a later release; overall likely the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:01.967208Z\", \"row_index\": 327, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1116.164207458496, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 57, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Lion in Winter\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Lion in Winter\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles match exactly; dates are close (years differ by 1) common for productions/editions; likely same work with different release year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:04.065791Z\", \"row_index\": 328, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2094.5839881896973, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 46, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Funny Girl\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Funny Girl\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title, only the year differs by one; likely same work with release year discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:05.603319Z\", \"row_index\": 329, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1533.5278511047363, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 52, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"In the Heat of the Night\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"In the Heat of the Night\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.71, \\\"explanation\\\": \\\"Titles match exactly; dates differ by year but likely referring to same work with different date reference, consider as same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:06.911134Z\", \"row_index\": 330, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1303.8229942321777, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 56, \"total_tokens\": 274, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Guess Who's Coming to Dinner\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Guess Who\\ufffds Coming to Dinner\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.74, \\\"explanation\\\": \\\"Titles are effectively the same film with a minor typographical quote difference; dates differ by year but could reflect release year vs. production year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:09.223392Z\", \"row_index\": 331, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2308.260440826416, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 221, \"output_tokens\": 58, \"total_tokens\": 279, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Who's Afraid of Virginia Woolf?\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Who\\ufffds Afraid of Virginia Woolf\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.68, \\\"explanation\\\": \\\"Titles are essentially the same work with a minor typographic difference in apostrophe; dates differ by one year but could reflect release vs. publication date.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:10.819112Z\", \"row_index\": 332, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1591.719150543213, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 64, \"total_tokens\": 280, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Man for All Seasons\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Man for All Seasons\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.76, \\\"explanation\\\": \\\"Same title with only a one-year date difference; could refer to the same work (film) released in different years or data error; high likelihood they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:12.279163Z\", \"row_index\": 333, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1457.0510387420654, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cat Ballou\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cat Ballou\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.21, \\\"explanation\\\": \\\"Same title but different release year (1965 vs 1966) suggests different works or editions; insufficient overlap to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:13.530967Z\", \"row_index\": 334, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1247.8053569793701, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"My Fair Lady\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"My Fair Lady\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title appears; dates differ by year, but could be different release years or editions; enough overlap to consider same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:15.206074Z\", \"row_index\": 335, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1670.1059341430664, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 53, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Lilies of the Field\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Lilies of the Field\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but dates differ by one year, which could indicate different editions or a different work; insufficient evidence of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:16.922709Z\", \"row_index\": 336, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1712.6352787017822, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 48, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"To Kill a Mockingbird\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"To Kill a Mockingbird\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Same title; dates differ by one year, likely edition/publication year variance for the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:18.287462Z\", \"row_index\": 337, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1360.7540130615234, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Miracle Worker\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Miracle Worker\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title with only a one-year date discrepancy; likely the same work (film/stage production) released across years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:19.666004Z\", \"row_index\": 338, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1374.5415210723877, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 215, \"output_tokens\": 43, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Walk on the Wild Side\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates strongly suggest different works; no clear overlap in attributes.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:20.747840Z\", \"row_index\": 339, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1077.836275100708, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 49, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Identical title with only a one-year date difference; likely same work with differing edition/publication year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:22.360697Z\", \"row_index\": 340, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1609.8566055297852, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 52, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Judgment at Nuremberg\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Judgment at Nuremburg\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles are highly similar with a minor spelling variant; dates differ by one year but refer to the same film/book commonly.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:23.982309Z\", \"row_index\": 341, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1618.6139583587646, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 47, \"total_tokens\": 257, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Two Women\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Two Women\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates suggests different works or editions; lack of additional identifying details keeps uncertainty.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:25.963676Z\", \"row_index\": 342, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1977.3674011230469, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 47, \"total_tokens\": 261, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Elmer Gantry\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Elmer Gantry\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same title with one-year date difference; likely the same work with publication/edition year discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:27.474175Z\", \"row_index\": 343, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1507.5008869171143, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 54, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Butterfield 8\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Butterfield 8\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title; dates differ by one year, which could reflect different editions or release years; but other fields matching suggests same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:29.116106Z\", \"row_index\": 344, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1637.9318237304688, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 52, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"High Note\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates are different (High Note vs High Noon; 1960 vs 1953), indicating different entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:31.132971Z\", \"row_index\": 345, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2012.8614902496338, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles match but the dates differ by year; the 1952 vs 1953 date suggests different releases/editions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:32.620403Z\", \"row_index\": 346, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1483.4320545196533, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 61, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Room at the Top\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Room at the Top\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Identical title with close but different dates; could refer to the same work released in different years or a re-release. The ambiguity keeps score moderate rather than definite.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:34.647467Z\", \"row_index\": 347, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2023.064136505127, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 53, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Separate Tables\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Separate Tables\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but the dates differ by a year, suggesting different works (likely different films/books) rather than the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:36.316924Z\", \"row_index\": 348, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1665.4558181762695, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 57, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"I Want to Live!\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"I Want to Live!\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different year; could be a different release or edition with close dates. The strong title match supports same entity with uncertainty about year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:37.916946Z\", \"row_index\": 349, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1596.0264205932617, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 220, \"output_tokens\": 53, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Bridge on the River Kwai\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Bridge On The River Kwai\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.78, \\\"explanation\\\": \\\"Titles differ only in capitalization; dates are close (1957 vs 1958) likely same film with release date variance.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:39.452053Z\", \"row_index\": 350, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1532.1073532104492, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 40, \"total_tokens\": 256, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Brave One\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Bridge On The River Kwai\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles and different dates; unlikely same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:42.024823Z\", \"row_index\": 351, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2569.0999031066895, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 58, \"total_tokens\": 274, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Three Faces of Eve\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Three Faces of Eve\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Identical title with only a one-year date difference; could be same work with release date discrepancy. Date mismatch reduces confidence but is common in records.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:43.071903Z\", \"row_index\": 352, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1043.0796146392822, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 50, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The King and I\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The King and I\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different year; likely the same work with release year discrepancy (original Broadway vs film/production).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:45.474311Z\", \"row_index\": 353, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2399.4054794311523, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Rose Tattoo\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Rose Tattoo\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title and close production year; minor date discrepancy likely due to publication vs. premiere date.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:47.020597Z\", \"row_index\": 354, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1542.2866344451904, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 56, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"On the Waterfront\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"On The Waterfront\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Titles are highly similar but differ by one-letter case and a year difference; the date discrepancy suggests they may refer to different works or editions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:53.161719Z\", \"row_index\": 355, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 6136.1260414123535, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 55, \"total_tokens\": 267, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Country Girl\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Country Girl\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title with different dates; could be same work with different publication year or editions. Moderate confidence that they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:55.543778Z\", \"row_index\": 356, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2378.058433532715, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 59, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Stalag 17\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Stalag 17\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Both records share the same title but have different dates; this could refer to different works or editions, but the date discrepancy reduces confidence of a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:57.756621Z\", \"row_index\": 357, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2208.8446617126465, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 56, \"total_tokens\": 274, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Come Back, Little Sheba\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Come Back, Little Sheba\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year, which could be release vs. production year or publication; core entity likely the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:51:59.207932Z\", \"row_index\": 358, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1447.8058815002441, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The African Queen\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The African Queen\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release year; could be same film with different release dates or a different work; insufficient to confirm.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:00.732591Z\", \"row_index\": 359, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1521.6593742370605, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 52, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Streetcar Named Desire\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Streetcar Named Desire\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be release year variance; likely same work with different listing year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:02.472732Z\", \"row_index\": 360, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1737.138032913208, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 48, \"total_tokens\": 258, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Born Yesterday\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Born Yesterday\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different release year (1950 vs 1951); likely different works or editions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:03.834620Z\", \"row_index\": 361, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1357.8882217407227, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 57, \"total_tokens\": 271, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"All the King's Men\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"All the King's Men\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title with only a one-year date difference suggesting different release years of the same work (film vs. publication); likely same entity across records.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:05.096464Z\", \"row_index\": 362, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1256.8459510803223, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 56, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Heiress\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Heiress\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title but different dates; could refer to different release years of the same work or a discrepancy in data quality, but likely related work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:07.641819Z\", \"row_index\": 363, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2542.3521995544434, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 56, \"total_tokens\": 268, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Johnny Belinda\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Johnny Belinda\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles match exactly; dates differ by a year which may reflect release vs. production or edition; insufficient to conclude different entity given identical title.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:08.831283Z\", \"row_index\": 364, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1185.4639053344727, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Double Life\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Double Life\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles are identical but dates differ by one year; could be different works or editions. Insufficient to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:11.103643Z\", \"row_index\": 365, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2268.357515335083, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 50, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Farmer's Daughter\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Farmer\\ufffds Daughter\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are nearly identical but dates differ by a year; insufficient to confirm same entity without additional corroborating data.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:12.624172Z\", \"row_index\": 366, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1517.5292491912842, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 224, \"output_tokens\": 51, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Mouse\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ between 'Mr. Mouse' and 'Mr. Hyde', and dates are different, suggesting distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:14.642120Z\", \"row_index\": 367, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2013.9477252960205, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 224, \"output_tokens\": 46, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles are identical but dates refer to different film release years, suggesting different works or versions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:16.492945Z\", \"row_index\": 368, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1846.825122833252, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 224, \"output_tokens\": 49, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.68, \\\"explanation\\\": \\\"Titles match exactly; dates differ by two years which could be different editions or releases of the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:17.678864Z\", \"row_index\": 369, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1180.9182167053223, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 217, \"output_tokens\": 37, \"total_tokens\": 254, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened on Fifth Avenue\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and dates; likely different films.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:18.750372Z\", \"row_index\": 370, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1067.5082206726074, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 216, \"output_tokens\": 54, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which may be due to release year vs. catalog year; likely the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:20.091863Z\", \"row_index\": 371, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1338.4885787963867, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 62, \"total_tokens\": 280, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Best Years of Our Lives\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Best Years of Our Lives\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Similar title with minor pluralization/word order; dates differ by one year but could reflect release/recording vs release date discrepancy; enough similarity to consider same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:21.858557Z\", \"row_index\": 372, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1763.6933326721191, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 52, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"To Each His Own\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"To Each His Own\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match but dates differ by one year, suggesting different productions or releases; insufficient evidence they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:23.359790Z\", \"row_index\": 373, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1497.2329139709473, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 51, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Lost Weekend\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Lost Weekend\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Titles match but dates differ by a year; could refer to different editions or errors, insufficient to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:24.639559Z\", \"row_index\": 374, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1275.7682800292969, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 56, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mildred Pierce\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mildred Pierce\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could reflect release date variance in sources; likely same work with different cataloged release dates.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:26.617829Z\", \"row_index\": 375, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1975.2702713012695, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Going My Way\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Going My Way\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be release year variation; likely same work with inconsistent date metadata.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:28.045733Z\", \"row_index\": 376, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1423.9044189453125, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 220, \"output_tokens\": 57, \"total_tokens\": 277, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Yankee Doodle Dandy\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Yankee Doodle Dandy\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Titles are identical; dates differ by one year which could be release vs production or archival date; overall high likelihood they refer to the same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:29.778051Z\", \"row_index\": 377, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1727.3125648498535, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 56, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mrs. Miniver\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mrs. Miniver\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles match, but dates differ by year (1942 vs 1943), suggesting different works or editions; insufficient to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:31.318481Z\", \"row_index\": 378, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1537.4302864074707, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 50, \"total_tokens\": 262, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sergeant York\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Sergeant York\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title with different release years; likely referring to the same film with a release year discrepancy or re-release.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:33.037563Z\", \"row_index\": 379, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1716.0828113555908, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 51, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Philadelphia Story\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Philadelphia Story\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates (1940 vs 1941); could be different editions or releases, uncertain alignment.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:34.733240Z\", \"row_index\": 380, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1691.676139831543, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 51, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kitty Foyle\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kitty Foyle\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Titles match exactly; dates are close (likely edition or release year variation) suggesting same work with different publication dates.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:36.204447Z\", \"row_index\": 381, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1467.207908630371, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 211, \"output_tokens\": 52, \"total_tokens\": 263, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boom Town\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ ('Boom Town' vs 'Boys Town') and dates are close but not identical; likely distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:37.643181Z\", \"row_index\": 382, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1434.734582901001, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 66, \"total_tokens\": 278, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.61, \\\"explanation\\\": \\\"Both records share the same title; differing year (1938 vs 1939) could reflect edition, release date, or misrecorded data, but the core entity appears the same.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:39.226751Z\", \"row_index\": 383, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1579.5691013336182, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 61, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gone with the Wind\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gone With the Wind\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.63, \\\"explanation\\\": \\\"Titles differ by capitalization and slight wording ('With' vs 'with'), but refer to the same famous work; dates differ by one year likely edition or publication variant.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:40.436967Z\", \"row_index\": 384, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1206.2273025512695, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 219, \"output_tokens\": 54, \"total_tokens\": 273, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Lives of Elizabeth and Essex\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different film titles and dates indicate distinct works; 'Elizabeth and Essex' vs 'Henry VIII' refer to different subjects and productions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:42.207800Z\", \"row_index\": 385, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1767.8325176239014, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 220, \"output_tokens\": 50, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Life of the Gannets\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Titles refer to different subjects (gannets vs. Henry VIII); dates also differ, indicating distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:44.685658Z\", \"row_index\": 386, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2474.8589992523193, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 218, \"output_tokens\": 52, \"total_tokens\": 270, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same work title with similar but not identical dates; likely the same film with a misrecorded or different release year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:46.589688Z\", \"row_index\": 387, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1900.0308513641357, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 47, \"total_tokens\": 259, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Jezebel\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Jezebel\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.44, \\\"explanation\\\": \\\"Same title but different year suggests different works or editions; insufficient overlap to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:48.059883Z\", \"row_index\": 388, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1466.1931991577148, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 214, \"output_tokens\": 51, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Captains Courageous\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Captains Courageous\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Titles match exactly; the one-year date difference could reflect release vs production date or edition variance, suggesting same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:49.868999Z\", \"row_index\": 389, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1806.117296218872, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 52, \"total_tokens\": 264, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Good Earth\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Good Earth\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.72, \\\"explanation\\\": \\\"Titles match exactly; dates differ by one year which could be edition or publication variation; overall strong likelihood of same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:51.947374Z\", \"row_index\": 390, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2074.373722076416, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 210, \"output_tokens\": 59, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morning Glory\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Morning Glory\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Titles match exactly but dates differ by two years; could be same work released in different years or a related record, but insufficient to distinguish without additional identifiers.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:54.061098Z\", \"row_index\": 391, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2110.722303390503, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 57, \"total_tokens\": 269, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Free Soul\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Free Soul\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title but different dates; could be the same work with a misdated or differently released version. Overall enough similarity to consider as same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:55.983919Z\", \"row_index\": 392, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1918.8203811645508, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 63, \"total_tokens\": 275, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Min and Bill\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Min and Bill\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.7, \\\"explanation\\\": \\\"Both records have the same title 'Min and Bill' but different dates (1930 vs 1932); could refer to the same work with differing release/production dates.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:52:58.049174Z\", \"row_index\": 393, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2061.256170272827, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 48, \"total_tokens\": 260, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Divorcee\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Divorcee\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates; could be different works or editions; insufficient to confirm a single entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:53:00.236189Z\", \"row_index\": 394, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2184.014320373535, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 54, \"total_tokens\": 266, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"In Old Arizona\\\", \\\"date\\\": \\\"1928-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"In Old Arizona\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.32, \\\"explanation\\\": \\\"Titles are the same, but the dates differ by two years, suggesting different releases or editions; insufficient evidence to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:53:01.699937Z\", \"row_index\": 395, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1459.749460220337, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 212, \"output_tokens\": 53, \"total_tokens\": 265, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Same title but different dates (1927 vs 1929) suggest different works or editions; insufficient to confirm same entity.\\\"}\"}\n" ] } ], "source": [ "# Run LLM-based matching\n", "# IMPORTANT: This cell will make API calls and incur costs\n", "# Comment out if you don't want to run LLM matching\n", "\n", "print(\"Running LLM-based matching...\\n\")\n", "print(\"(This may take several minutes depending on the number of candidates)\\n\")\n", "\n", "correspondences_llm = llm_matcher.match(\n", " df_left=df_academy,\n", " df_right=df_actors,\n", " candidates=blocker_standard,\n", " chat_model=chat_model,\n", " fields=attributes_for_llm,\n", " id_column='id',\n", " out_dir= OUTPUT_DIR / \"llm\",\n", " debug=True\n", ")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 26\n", "[INFO ] root - True Negatives: 100\n", "[INFO ] root - False Positives: 0\n", "[INFO ] root - False Negatives: 21\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.857\n", "[INFO ] root - Precision: 1.000\n", "[INFO ] root - Recall: 0.553\n", "[INFO ] root - F1-Score: 0.712\n" ] } ], "source": [ "# Evaluate LLM-based matching results\n", "\n", "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=correspondences_llm,\n", " test_pairs=df_validation,\n", " out_dir= OUTPUT_DIR / \"llm\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When inspecting the log files in data/output/llm, we can see that the LLM often decides for non-match due to the differences in release year that was already impacting our earlier RuleBasedMatcher.\n", "\n", "We could either\n", "\n", "- remove the date attribute\n", "- make the LLM aware of problems with the date attribute by passing a custom prompt that overwrites PyDIs standard prompt using the \"system_prompt\" parameter\n", "- provide few-shot examples from which the LLM can learn this data quality issue\n", "\n", "Let's try using few-shot prompting to show this functionality. The following examples are selected from our training set saved in **df_train**. They mimic the exact output format that is expected as defined in PyDI's standard prompt." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "few_shot_examples = [\n", " # POSITIVE 1: Same movie \"7th Heaven\" but 2 years difference\n", " (\n", " {\"title\": \"7th Heaven\", \"date\": \"1927-01-01\"},\n", " {\"title\": \"7th Heaven\", \"date\": \"1929-01-01\"},\n", " {\"match\": \"true\", \"score\": 0.95, \"explanation\": \"Same movie with identical title despite 2-year date discrepancy\"}\n", " ),\n", " \n", " # POSITIVE 2: Same movie \"It Happened One Night\" but 1 year difference\n", " (\n", " {\"title\": \"It Happened One Night\", \"date\": \"1934-01-01\"},\n", " {\"title\": \"It Happened One Night\", \"date\": \"1935-01-01\"},\n", " {\"match\": \"true\", \"score\": 0.95, \"explanation\": \"Same movie with identical title despite 1-year date difference\"}\n", " ),\n", " \n", " # NEGATIVE 1: \"All the President's Men\" vs \"All the King's Men\" - very similar titles but different movies\n", " (\n", " {\"title\": \"Goodbye, Mr. Chips\", \"date\": \"1969-01-01\"},\n", " {\"title\": \"Goodbye, Mr. Chips\", \"date\": \"1940-01-01\"},\n", " {\"match\": \"false\", \"score\": 0.1, \"explanation\": \"Different movie versions despite identical title - 29-year gap indicates remake\"}\n", " ),\n", " \n", " # NEGATIVE 2: \"A Stolen Life\" vs \"A Double Life\" - both have \"A ... Life\" pattern\n", " (\n", " {\"title\": \"Back Street\", \"date\": \"1961-01-01\"},\n", " {\"title\": \"Wall Street\", \"date\": \"1988-01-01\"},\n", " {\"match\": \"false\", \"score\": 0.2, \"explanation\": \"Different movies despite both having Street - Back Street vs Wall Street\"}\n", " )\n", "]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Entity matching: academy_awards (4580 records) <-> actors (149 records)\n", "[INFO ] root - Processing 1 candidate batches\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Running LLM-based matching with few-shot examples...\n", "\n", "(This may take several minutes depending on the number of candidates)\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:34.280107Z\", \"row_index\": 0, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1649.5249271392822, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 49, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different films released in 1970 and 2010; likely distinct works with same name\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:36.546623Z\", \"row_index\": 1, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2263.516426086426, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 42, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"True Grit\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.88, \\\"explanation\\\": \\\"Same title; different year likely same film release across different markets or formats\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:37.700014Z\", \"row_index\": 2, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1150.3944396972656, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gasland\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with similar words; unlikely same entity across decades\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:38.933986Z\", \"row_index\": 3, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1230.9715747833252, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gattaca\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years; no evidence of aliasing between Gattaca and Gaslight\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:41.154432Z\", \"row_index\": 4, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2217.447280883789, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 49, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gagarin\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no clear identity linkage between 'Gagarin' and 'Gaslight'.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:42.388887Z\", \"row_index\": 5, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1231.4543724060059, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 36, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gandhi\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no plausible overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:43.459758Z\", \"row_index\": 6, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1066.87593460083, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 44, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gambit\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with distinct genres/plots; no evidence of being the same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:44.937640Z\", \"row_index\": 7, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1474.881649017334, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 83, \"total_tokens\": 644, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gaslight\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but year differs by 1 year; could be sequel/remake, but commonly refers to Gaslight (1944) and Gaslight (1945) remakes not identical release years; ambiguity leans toward potential same story, but differing production years reduce confidence.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:46.403687Z\", \"row_index\": 8, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1462.047815322876, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 43, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Warriors of Qiugang\\\", \\\"date\\\": \\\"2010-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Way of All Flesh & The Las\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Significantly different titles and eras; unlikely to refer to the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:48.236386Z\", \"row_index\": 9, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1828.6993503570557, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 41, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The War of the Worlds\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Way of All Flesh & The Las\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and eras; no evidence they refer to same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:50.181235Z\", \"row_index\": 10, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1941.8604373931885, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coraline\\\", \\\"date\\\": \\\"2009-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different (Coraline vs Coquette) with vastly different dates; no plausible match\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:51.421909Z\", \"row_index\": 11, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1237.6735210418701, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 36, \"total_tokens\": 596, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Collateral\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and eras; no plausible overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:53.183449Z\", \"row_index\": 12, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1758.5408687591553, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 37, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Contact\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no reasonable overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:54.923237Z\", \"row_index\": 13, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1736.7873191833496, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Contact\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Distinct titles and dates; no evident overlap referring to same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:56.458411Z\", \"row_index\": 14, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1532.067060470581, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 41, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cocoon\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different; no indication they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:57.452817Z\", \"row_index\": 15, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 990.4065132141113, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 37, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Country\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no clear overlap; years unrelated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:57:58.811870Z\", \"row_index\": 16, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1355.053186416626, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 43, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Confidence\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with large date gap; no basis to link them as same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:00.256115Z\", \"row_index\": 17, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1441.2455558776855, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cowboy\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and no contextual link between Cowboy (1966) and Coquette (1930)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:01.707074Z\", \"row_index\": 18, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1447.9591846466064, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cowboy\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and widely different dates imply different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:03.170747Z\", \"row_index\": 19, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1460.6728553771973, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 50, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Conquest\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and years; Conquest (1937) and Coquette (1930) refer to distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:04.379547Z\", \"row_index\": 20, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1205.801248550415, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1928-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coquette\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years suggest different films; potential remakes or sequels not strongly indicated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:05.978864Z\", \"row_index\": 21, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1596.3168144226074, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 47, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Milk\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to different works (Milk vs Misery) with different years; unlikely the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:07.680497Z\", \"row_index\": 22, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1698.6303329467773, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 44, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same title; one-year difference likely due to release year variation for the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:09.556969Z\", \"row_index\": 23, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1873.4707832336426, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 44, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Missing\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Misery\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles differ significantly; 'Missing' vs 'Misery' refer to different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:10.608682Z\", \"row_index\": 24, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1047.712802886963, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Changeling\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.38, \\\"explanation\\\": \\\"Different titles (Changeling vs Charly) and different years; unlikely same real-world entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:12.126333Z\", \"row_index\": 25, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1513.6497020721436, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 38, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chicago\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles with no overlap; unlikely same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:13.546272Z\", \"row_index\": 26, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1415.9424304962158, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chocolat\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles with no strong linking information; unrelated works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:15.023504Z\", \"row_index\": 27, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1474.2298126220703, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 41, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Character\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated release years; no strong evidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:16.421447Z\", \"row_index\": 28, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1394.9425220489502, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chaplin\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different titles and non-overlapping release years; not the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:20.055270Z\", \"row_index\": 29, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 3629.823684692383, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 57, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charade\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years; 'Charade' (1963) vs 'Charly' (1968) are distinct films with different plots\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:21.418737Z\", \"row_index\": 30, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1360.4671955108643, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chinatown\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles with different years; no evidence they refer to same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:22.564788Z\", \"row_index\": 31, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1142.0514583587646, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 51, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but 1-year difference could indicate different adaptations or release years; risk of same-named work but uncertain\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:24.066268Z\", \"row_index\": 32, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1498.4807968139648, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 45, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Chagall\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different years; unlikely same film (Chagall vs Charly)\\\" }\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:25.753815Z\", \"row_index\": 33, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1684.546947479248, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 58, \"total_tokens\": 619, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Charade\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles with different release years; 'Charade' (1963) vs 'Charly' (1968/1969) are distinct films\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:27.004542Z\", \"row_index\": 34, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1247.7283477783203, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 38, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Champion\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Charly\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and large date gap; unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:28.481420Z\", \"row_index\": 35, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1472.876787185669, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 40, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Conscience of Nhem En\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles refer to different works with unrelated content and very different years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:29.774216Z\", \"row_index\": 36, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1289.7968292236328, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 566, \"output_tokens\": 42, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Collector of Bedford Street\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles refer to different works with different themes and dates; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:31.293018Z\", \"row_index\": 37, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1515.8016681671143, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 574, \"output_tokens\": 44, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Colours of My Father: A Portrait of Sam Borenstein\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.22, \\\"explanation\\\": \\\"Titles are different (long documentary portrait vs The Color of Money) and years unrelated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:32.830079Z\", \"row_index\": 38, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1534.0602397918701, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 71, \"total_tokens\": 636, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but one-year difference; could be sequel/remake but likely distinct work (The Color of Money is 1986 film directed by Scorsese; 1987 may be release regional but year mismatch).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:34.410716Z\", \"row_index\": 39, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1577.6374340057373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 37, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Court-Martial of Billy Mitchell\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no strong overlap; unrelated works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:35.702003Z\", \"row_index\": 40, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1288.2881164550781, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 566, \"output_tokens\": 42, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Conquest of Everest\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Color of Money\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different works with unrelated titles and release years; no overlap suggesting same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:37.197069Z\", \"row_index\": 41, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1492.0661449432373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pig\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and release years; no plausible alias.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:38.919944Z\", \"row_index\": 42, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1719.8750972747803, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pig\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no apparent overlap; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:40.613981Z\", \"row_index\": 43, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1691.0386085510254, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 50, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Different titles and release years suggest different works (The Pianist 2002 vs The Piano 1994)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:41.847514Z\", \"row_index\": 44, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1230.043649673462, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 42, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film title; consecutive years likely due to release year variation in records\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:43.328516Z\", \"row_index\": 45, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1478.001594543457, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years suggesting different films; uncertain without additional metadata.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:44.667471Z\", \"row_index\": 46, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1335.95609664917, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 45, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"The Piano vs The Pianist are distinct works with different titles and likely different productions.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:46.020775Z\", \"row_index\": 47, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1350.3036499023438, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pirate\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Piano\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no contextual overlap based on available data\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:48.121681Z\", \"row_index\": 48, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2096.909284591675, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 37, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pirate\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Pianist\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated dates; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:49.632310Z\", \"row_index\": 49, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1506.6287517547607, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 38, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Happy-Go-Lucky\\\", \\\"date\\\": \\\"2008-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Very different titles and eras; no compelling overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:51.234950Z\", \"row_index\": 50, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1599.639892578125, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hardwood\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles; no strong overlap in year or context to indicate same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:52.687301Z\", \"row_index\": 51, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1449.350357055664, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 48, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Same title but with a large date gap and likely different adaptations (1996 vs 1949).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:56.215122Z\", \"row_index\": 52, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 3524.822235107422, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different production years suggest different adaptations (possible multiple films), uncertainty remains but not enough to confirm\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:58:58.577594Z\", \"row_index\": 53, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2359.4696521759033, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Havana\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and non-overlapping release years; no basis for same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:00.616362Z\", \"row_index\": 54, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2035.7675552368164, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 48, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hanussen\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles with unrelated dates; 'Hanussen' and 'Hamlet' refer to distinct works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:02.698544Z\", \"row_index\": 55, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2078.1803131103516, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 37, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harvest\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated contexts and widely separated dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:04.352038Z\", \"row_index\": 56, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1649.493932723999, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hawaii\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no corroborating details; dates and subjects do not align\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:05.603259Z\", \"row_index\": 57, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1248.2221126556396, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hatari!\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles; even with single-word similarity none significant\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:07.111638Z\", \"row_index\": 58, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1505.378246307373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harvey\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated dates; unlikely to be the same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:08.968251Z\", \"row_index\": 59, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1853.6148071289062, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hamlet\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title with consecutive years could be different productions; insufficient to confirm same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:10.283446Z\", \"row_index\": 60, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1310.192346572876, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 36, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ratatouille\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years indicate distinct films\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:12.287595Z\", \"row_index\": 61, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2001.1465549468994, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 47, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title and closely related release years for the same person/subject; likely the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:13.544561Z\", \"row_index\": 62, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1252.9733180999756, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 44, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ran\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ significantly (Ran vs Ray); unlikely same entity despite both being film titles\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:15.366661Z\", \"row_index\": 63, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1819.0996646881104, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ragtime\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no clear alias; unrelated works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:17.240411Z\", \"row_index\": 64, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1870.750904083252, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 47, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raoni\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles ('Raoni' vs 'Ray') and large date gap; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:18.774586Z\", \"row_index\": 65, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1531.181812286377, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 55, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Rashomon\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; 'Rashomon' (1950s Japanese film) vs 'Ray' (2004 biopic)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:20.225362Z\", \"row_index\": 66, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1447.7736949920654, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 39, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raffles\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ray\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated dates; unlikely same real-world entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:21.749695Z\", \"row_index\": 67, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1520.3325748443604, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 36, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beaufort\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different films with distinct titles and eras\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:24.045128Z\", \"row_index\": 68, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2292.4323081970215, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beloved\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to different works with different years; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:26.114234Z\", \"row_index\": 69, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2066.1063194274902, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 41, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beaches\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no plausible connection based on common keywords; dates unrelated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:27.246981Z\", \"row_index\": 70, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1128.7462711334229, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 37, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Beetlejuice\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and genres; no plausible entity match\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:28.585235Z\", \"row_index\": 71, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1335.2530002593994, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 53, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Betrayal\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles refer to very different works; Betrayal (1983) vs Ben-Hur (1960) are unrelated.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:29.961468Z\", \"row_index\": 72, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1373.2340335845947, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 55, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Benji\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles with no plausible aliasing; Benji (1974) vs Ben-Hur (1960) refer to different entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:31.502270Z\", \"row_index\": 73, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1537.801742553711, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ben\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles are clearly different (Ben vs Ben-Hur); unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:32.877428Z\", \"row_index\": 74, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1372.1556663513184, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 41, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Becket\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated release years; no strong evidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:35.199792Z\", \"row_index\": 75, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2318.3653354644775, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 66, \"total_tokens\": 629, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different release year by one year could be a typo, but typically Ben-Hur (1959) and Ben-Hur (1960) refer to distinct productions; ambiguity but likely different.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:36.341775Z\", \"row_index\": 76, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1137.9854679107666, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 45, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Benjy\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ben-Hur\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Very different titles; 'Benjy' vs 'Ben-Hur' unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:38.980616Z\", \"row_index\": 77, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2635.840892791748, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 41, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mongol\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated genres/periods; no overlap in identity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:40.668331Z\", \"row_index\": 78, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1684.7155094146729, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mongol\\\", \\\"date\\\": \\\"2007-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ (\\\"Mongol\\\" vs \\\"Monster\\\"); unrelated works with different release years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:42.296198Z\", \"row_index\": 79, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1623.8665580749512, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and distinct release years; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:44.340188Z\", \"row_index\": 80, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2039.9901866912842, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 54, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title with different release years; could be same film in different markets or sequel/remake, but year difference makes ambiguity moderate.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:46.056491Z\", \"row_index\": 81, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1713.303804397583, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 44, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"More\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no obvious relation; years close but not enough to suggest same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:47.778082Z\", \"row_index\": 82, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1717.5910472869873, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 41, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"More\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ significantly ('More' vs 'Monster'); unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:49.485544Z\", \"row_index\": 83, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1704.4627666473389, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 39, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film title with consecutive years; highly likely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:51.157107Z\", \"row_index\": 84, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1668.5714721679688, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no obvious alias or relation; Moonstruck vs Monster refer to different films\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:52.955401Z\", \"row_index\": 85, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1795.2940464019775, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 51, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonraker\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Different titles ('Moonraker' vs 'Moonstruck') and years; no strong overlap to indicate same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:54.322734Z\", \"row_index\": 86, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1364.3345832824707, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonraker\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated dates; no strong similarity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:55.815668Z\", \"row_index\": 87, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1489.9344444274902, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morgan!\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no plausible match; Morgan! vs Moonstruck.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:56.981459Z\", \"row_index\": 88, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1162.7922058105469, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 41, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morgan!\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles clearly different (Morgan! vs Monster); unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T09:59:58.458109Z\", \"row_index\": 89, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1473.660945892334, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 53, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morituri\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles with no overlapping identifiers; Morituri (1965) vs Moonstruck (1988) are distinct films\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:00.152769Z\", \"row_index\": 90, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1691.2736892700195, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morituri\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no overlap; unlikely same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:01.346245Z\", \"row_index\": 91, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1190.4780864715576, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 47, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonbird\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different (Moonbird vs Moonstruck) with large date gap; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:03.187233Z\", \"row_index\": 92, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1837.9883766174316, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonbird\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles with no alignment in date or obvious aliasing\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:04.452275Z\", \"row_index\": 93, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1262.0418071746826, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 41, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mogambo\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no clear overlap; release years far apart and unrelated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:06.730571Z\", \"row_index\": 94, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2275.306224822998, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mogambo\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different and years widely separated; unlikely to refer to same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:07.769654Z\", \"row_index\": 95, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1036.083459854126, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonrise\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles; Moonrise vs Moonstruck are distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:08.737712Z\", \"row_index\": 96, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 965.0571346282959, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moonrise\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping release periods; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:10.123324Z\", \"row_index\": 97, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1382.6143741607666, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moontide\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different (Moontide vs Moonstruck) and genres/eras differ.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:11.852268Z\", \"row_index\": 98, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1725.9435653686523, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 51, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Moontide\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no overlap; 1942 film Moontide and 2004 film Monster refer to distinct entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:13.912256Z\", \"row_index\": 99, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2056.987762451172, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 42, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morocco\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Moonstruck\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different films by title and era; no basis for same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:15.690104Z\", \"row_index\": 100, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1773.8516330718994, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 38, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morocco\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monster\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and eras; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:17.267505Z\", \"row_index\": 101, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1573.401689529419, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 36, \"total_tokens\": 596, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cars\\\", \\\"date\\\": \\\"2006-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles and release years indicate different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:18.966983Z\", \"row_index\": 102, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1696.4709758758545, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 45, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Capote\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles referring to distinct works (Capote vs Cabaret) with different release years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:20.481224Z\", \"row_index\": 103, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1511.240005493164, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cashback\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; Cashback (2005) vs Cabaret (1973) refer to distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:21.742789Z\", \"row_index\": 104, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1258.559226989746, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caravan\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no clear overlap; no matching date proximity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:22.613729Z\", \"row_index\": 105, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 866.9390678405762, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Canhead\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and era; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:23.770577Z\", \"row_index\": 106, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1151.843547821045, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 43, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casino\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different years; no strong indication they refer to the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:25.634439Z\", \"row_index\": 107, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1860.865592956543, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camila\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different years; no evident overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:27.384342Z\", \"row_index\": 108, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1746.903419494629, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 36, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carmen\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping release years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:28.599714Z\", \"row_index\": 109, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1212.371826171875, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caravans\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no strong overlap in release year suggests different entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:30.229134Z\", \"row_index\": 110, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1626.4240741729736, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carrie\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with distinct release years; no evidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:33.085305Z\", \"row_index\": 111, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2853.1699180603027, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same title; one-year difference could be release year discrepancy for the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:34.900960Z\", \"row_index\": 112, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1811.6540908813477, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camelot\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly; unrelated works despite shared musical theme keywords\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:36.189495Z\", \"row_index\": 113, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1284.5354080200195, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Can-Can\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles with unrelated release years; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:37.474116Z\", \"row_index\": 114, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1280.6212902069092, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 42, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Career\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are clearly different (Career vs Cabaret); unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:38.663474Z\", \"row_index\": 115, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1186.356544494629, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carrie\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no indication of same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:40.522476Z\", \"row_index\": 116, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1856.0025691986084, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Caged\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly and years are far apart; unlikely same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:42.260784Z\", \"row_index\": 117, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1735.3057861328125, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 51, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casbah\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different ('Casbah' vs 'Cabaret') with large date gap; no strong evidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:43.961440Z\", \"row_index\": 118, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1696.6562271118164, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Casablanca\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and release dates; no plausible alias overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:45.724806Z\", \"row_index\": 119, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1759.3700885772705, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Carefree\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and eras; no plausible link.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:46.870350Z\", \"row_index\": 120, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1141.5469646453857, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Camille\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with distinct release years; no indication of the same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:48.205354Z\", \"row_index\": 121, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1332.002878189087, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 39, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cavalcade\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cabaret\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles referring to distinct films; no close matching attributes\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:49.792985Z\", \"row_index\": 122, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1584.6314430236816, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maestro\\\", \\\"date\\\": \\\"2006-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no overlap in likely identity; years differ substantially\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:51.052939Z\", \"row_index\": 123, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1255.9630870819092, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 56, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mal\\ufffdna\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles are clearly different (Mal\\\\u00f1a vs Marty) and separated by large date gap; no strong evidence of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:52.527622Z\", \"row_index\": 124, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1471.6835021972656, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Magnolia\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated release years; no overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:54.384019Z\", \"row_index\": 125, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1852.3967266082764, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mandela\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and distant dates; unlikely same real-world entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:56.594523Z\", \"row_index\": 126, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2207.5040340423584, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 41, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maverick\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years; unlikely to refer to the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:00:58.944371Z\", \"row_index\": 127, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2346.848249435425, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manipulation\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no clear relation between 'Manipulation' and 'Marty'\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:00.664504Z\", \"row_index\": 128, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1716.1328792572021, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Matewan\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and unrelated release years; not the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:02.945981Z\", \"row_index\": 129, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2278.477430343628, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maurice\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras (Maurice 1987 vs Marty 1956) unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:05.043582Z\", \"row_index\": 130, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2093.601942062378, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 39, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mannequin\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates; no strong similarity suggesting same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:06.622352Z\", \"row_index\": 131, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1575.7718086242676, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 42, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mask\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and publication years; no strong evidence of same real-world entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:09.045178Z\", \"row_index\": 132, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2419.8265075683594, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 42, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marlene\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"DIfferent titles; no obvious alias; dates also non-overlapping\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:11.015985Z\", \"row_index\": 133, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1967.8058624267578, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manhattan\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping release years; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:13.210126Z\", \"row_index\": 134, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2191.1420822143555, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mahogany\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years suggest different films.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:15.029670Z\", \"row_index\": 135, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1816.545009613037, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Manson\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles with no evident linkage; dates also differ significantly\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:16.482193Z\", \"row_index\": 136, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1449.5062828063965, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marjoe\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different titles and release years suggest distinct entities.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:19.359412Z\", \"row_index\": 137, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2874.2191791534424, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Madron\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Different titles with different years; no plausible aliasing\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:21.934753Z\", \"row_index\": 138, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2571.3417530059814, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marooned\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and dates, no indication of same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:23.926891Z\", \"row_index\": 139, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1990.1373386383057, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 44, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mandragola\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping release years; no strong indication of same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:25.286871Z\", \"row_index\": 140, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1356.9796085357666, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Macario\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years; no clear overlap to indicate the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:27.011662Z\", \"row_index\": 141, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1720.7872867584229, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 59, \"total_tokens\": 620, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title may refer to different film releases; one-year difference could be same film with release date variance we should check, but uncertainty leads to cautious non-match\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:28.529983Z\", \"row_index\": 142, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1514.3208503723145, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Madeline\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different works by different titles and years; no strong overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:30.497240Z\", \"row_index\": 143, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1964.2572402954102, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 41, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Marie-Louise\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different years; no strong overlap to indicate same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:31.949480Z\", \"row_index\": 144, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1448.2383728027344, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 37, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mannequin\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years; no plausible overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:33.471413Z\", \"row_index\": 145, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1518.935203552246, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 45, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Maytime\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Marty\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles; no compelling resemblance beyond common word 'time'/'Marty' notes\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:35.789012Z\", \"row_index\": 146, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2314.600944519043, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Match Point\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and unrelated release periods; no evidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:38.089251Z\", \"row_index\": 147, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2297.236442565918, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 55, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mary Poppins\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release year; potential same film released around 1964\\u20131965 but not enough to confirm, slight discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:39.978170Z\", \"row_index\": 148, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1884.918451309204, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 47, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Million Dollar Baby\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Million Dollar Baby\\\", \\\"date\\\": \\\"2005-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.9, \\\"explanation\\\": \\\"Same movie title with consecutive years likely same film (Million Dollar Baby, 2004 release).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:42.119852Z\", \"row_index\": 149, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2137.683629989624, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 39, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Incredibles\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and eras; no evidence of overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:43.920148Z\", \"row_index\": 150, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1797.2958087921143, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 42, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Insider\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; The Insider vs The Informer are distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:45.759943Z\", \"row_index\": 151, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1836.794376373291, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 37, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Invaders\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and years; no plausible identity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:47.628163Z\", \"row_index\": 152, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1865.2207851409912, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Informer\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same title with near-year difference likely the same film released around 1935\\u20131936\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:49.093834Z\", \"row_index\": 153, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1461.6706371307373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 46, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of the Weeping Camel\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and eras; unrelated subject matter (camel documentary vs Louis Pasteur biopic)\\\" }\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:51.167663Z\", \"row_index\": 154, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2070.8305835723877, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 39, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Statue of Liberty\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no overlap in subject or identifiers\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:52.562464Z\", \"row_index\": 155, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1390.8019065856934, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 40, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Adele H.\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different works with distinct titles and release periods; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:54.530511Z\", \"row_index\": 156, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1965.0473594665527, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 55, \"total_tokens\": 623, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Three Loves\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to different works (The Story of Three Loves vs The Story of Louis Pasteur) with different dates; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:56.683649Z\", \"row_index\": 157, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2149.1377353668213, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 49, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Time\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles refer to different subjects (The Story of Time vs The Story of Louis Pasteur) with different dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:58.103901Z\", \"row_index\": 158, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1416.2521362304688, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 37, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Dr. Wassell\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Distinct titles and release years suggest different works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:01:59.693012Z\", \"row_index\": 159, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1585.1216316223145, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 51, \"total_tokens\": 620, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Story of Louis Pasteur\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different release years; could be same film released across years or different editions, but uncertain without more data\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:01.386550Z\", \"row_index\": 160, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1690.5388832092285, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 49, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mystic River\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mystic River\\\", \\\"date\\\": \\\"2004-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be a data error or separate release/version but unlikely the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:02.940838Z\", \"row_index\": 161, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1550.288438796997, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.8, \\\"explanation\\\": \\\"Same title with minor date discrepancy; likely same entity (film)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:04.995112Z\", \"row_index\": 162, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2051.274299621582, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hospital\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated years; unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:06.941099Z\", \"row_index\": 163, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1942.9895877838135, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hole\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no overlap; years are far apart and imply distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:08.512185Z\", \"row_index\": 164, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1567.0855045318604, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 40, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Hoaxters\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Hours\\\", \\\"date\\\": \\\"2003-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles with no evident link to same real-world work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:10.002531Z\", \"row_index\": 165, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1487.3456954956055, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 50, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The ChubbChubbs!\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and eras; no evident connection between The ChubbChubbs! (short) and The Champ\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:11.246439Z\", \"row_index\": 166, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1240.907907485962, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 39, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Childeater\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with non-overlapping dates; unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:13.134002Z\", \"row_index\": 167, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1884.5620155334473, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different films with the same title but from different eras; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:14.483548Z\", \"row_index\": 168, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1345.545768737793, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Thursday's Children\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping dates indicate different entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:15.758587Z\", \"row_index\": 169, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1271.0371017456055, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Thousands Cheer\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different films with different titles and release years; no evidence of aliasing\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:17.603087Z\", \"row_index\": 170, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1841.5002822875977, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Champ\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Likely different film versions with similar title; 2-year gap suggests remake but still distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:19.845262Z\", \"row_index\": 171, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2239.1750812530518, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Training Day\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Training Day\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 1.0, \\\"explanation\\\": \\\"Identical title and date; exact same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:21.899327Z\", \"row_index\": 172, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2051.0635375976562, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 56, \"total_tokens\": 619, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Monster's Ball\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Monsters Ball\\\", \\\"date\\\": \\\"2002-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Apostrophe difference and year offset; could be confusion with Monster's Ball vs Monsters Ball, but dates differ and title differs in punctuation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:24.659858Z\", \"row_index\": 173, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2757.52854347229, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shrek\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different release years; no basis for same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:26.722205Z\", \"row_index\": 174, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2059.34739112854, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release year; likely different films with similar names; not enough to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:27.866076Z\", \"row_index\": 175, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1140.8720016479492, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 52, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shadowlands\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles and genres; no strong overlap between Shadowlands (1993) and Shine (1996/1997)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:29.803624Z\", \"row_index\": 176, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1934.5464706420898, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 56, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shoeshine\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles ('Shoeshine' vs 'Shine') likely refer to different works; dates 1987 vs 1997 also differ\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:31.722966Z\", \"row_index\": 177, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1916.3436889648438, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shampoo\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles; no strong overlap beyond generic 'Sh'/'ine'\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:33.354840Z\", \"row_index\": 178, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1628.8731098175049, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shanks\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly; unlikely same entity despite generic 'Sh'\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:35.104679Z\", \"row_index\": 179, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1746.8407154083252, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 35, \"total_tokens\": 596, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shaft\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and unrelated release years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:36.738987Z\", \"row_index\": 180, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1631.1516761779785, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 38, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shenandoah\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated dates; unlikely the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:38.922210Z\", \"row_index\": 181, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2179.222583770752, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 44, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shane\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ (Shane vs Shine) with large date gap; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:40.029754Z\", \"row_index\": 182, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1104.5446395874023, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 51, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shoe-Shine\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shine\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Titles differ significantly: 'Shoe-Shine' vs 'Shine' and large date gap; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:41.405385Z\", \"row_index\": 183, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1372.6322650909424, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 44, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Am\\ufffdlie\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly (Am\\u00e9lie vs Amadeus); unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:42.947678Z\", \"row_index\": 184, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1539.292812347412, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amistad\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different (Amistad vs Amadeus) despite both being movies; unrelated subjects and eras.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:44.722589Z\", \"row_index\": 185, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1771.8827724456787, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 37, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amazon\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Distinct titles with different semantics and no date alignment\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:47.336012Z\", \"row_index\": 186, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2610.422134399414, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 41, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title, consecutive years likely same film with minor release-year discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:48.755862Z\", \"row_index\": 187, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1416.2070751190186, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amarcord\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles (Amarcord vs Amadeus) with a 10-year gap; unlikely the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:50.689033Z\", \"row_index\": 188, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1930.1717281341553, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 43, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Amarcord\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Amadeus\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Titles differ significantly (Amarcord vs Amadeus) indicating different entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:52.179168Z\", \"row_index\": 189, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1486.1352443695068, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 51, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"the accountant\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly ('the accountant' vs 'The Accused') and refer to different works; dates far apart.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:54.236001Z\", \"row_index\": 190, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2052.833080291748, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 57, \"total_tokens\": 620, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Titles identical but year differs by 1; could be the same film if release across years, but more likely different records for adjacent release years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:56.304763Z\", \"row_index\": 191, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2065.763473510742, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 48, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Actress\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Accused\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are distinct and unlikely to refer to the same film; no overlapping data to support a match.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:57.700259Z\", \"row_index\": 192, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1391.4964199066162, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"true\\\", \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title with a one-year date difference; could be same film with different release dates in some sources.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:02:59.424413Z\", \"row_index\": 193, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1720.155954360962, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 42, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Glory\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and unrelated release years; no indication of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:01.384145Z\", \"row_index\": 194, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1955.7321071624756, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gloria\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles differ significantly; Gloria vs Gladiator refer to different entities\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:03.077598Z\", \"row_index\": 195, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1689.4538402557373, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Glass\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gladiator\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles; glass vs gladiator, different works and eras\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:04.434740Z\", \"row_index\": 196, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1354.142427444458, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 42, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Erin Brockovich\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Erin Brockovich\\\", \\\"date\\\": \\\"2001-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same film title with consecutive years; likely same movie with slight date variance\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:05.927111Z\", \"row_index\": 197, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1488.370418548584, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 63, \"total_tokens\": 624, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"American Beauty\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"American Beauty\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different release year could be same film with distribution differences; 1999 vs 2000 suggests possible different edit or release dates, but more likely different year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:07.406195Z\", \"row_index\": 198, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1476.0842323303223, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 56, \"total_tokens\": 621, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boys Don't Cry\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Don't Cry\\\", \\\"date\\\": \\\"2000-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be same film with date discrepancy, but 1-year difference suggests uncertainty; however likely different production years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:08.941994Z\", \"row_index\": 199, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1531.7988395690918, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Humdrum\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no evident relation; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:11.108237Z\", \"row_index\": 200, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2163.2425785064697, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 46, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hungarians\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ significantly ('Hungarians' vs 'Hud'); unrelated entities despite potential linguistic similarity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:12.818575Z\", \"row_index\": 201, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1706.3384056091309, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 37, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hunger\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release years with no clear overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:15.320421Z\", \"row_index\": 202, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2497.8458881378174, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 57, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title \\\"Hud\\\" but different release years; could be same film released in different markets or re-release, but year difference small suggests same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:17.646514Z\", \"row_index\": 203, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2322.0934867858887, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Humoresque\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Hud\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and distinct films both in era; no plausible link\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:21.307708Z\", \"row_index\": 204, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 3657.191514968872, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 52, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Life Is Beautiful\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Life is Beautiful\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Minor case variation only; different release years suggest different records but could be same but uncertain; output false due to year difference\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:22.971385Z\", \"row_index\": 205, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1660.677194595337, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 55, \"total_tokens\": 620, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Shakespeare in Love\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Shakespeare in Love\\\", \\\"date\\\": \\\"1999-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title with consecutive years; could be same film released across different markets or a similar title, but dataset likely differs by release year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:24.129915Z\", \"row_index\": 206, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1154.529094696045, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 39, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dancemaker\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different titles and era; no basis for same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:26.019546Z\", \"row_index\": 207, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1885.6291770935059, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 39, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dancemaker\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles and dates differ significantly; unlikely the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:28.047047Z\", \"row_index\": 208, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2024.5006084442139, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daylight\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no evident equivalence; years and genres likely do not align\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:29.568153Z\", \"row_index\": 209, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1517.0996189117432, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daylight\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and unrelated details; no clear entity match\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:30.899426Z\", \"row_index\": 210, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1327.2759914398193, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dave\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Dissimilar titles and widely different dates; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:32.288166Z\", \"row_index\": 211, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1385.7378959655762, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 37, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dave\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles with no strong overlap in data\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:34.002415Z\", \"row_index\": 212, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1711.247444152832, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Damage\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and non-overlapping release years; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:35.736034Z\", \"row_index\": 213, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1729.6192646026611, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 38, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Damage\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no plausible overlap in content or timeline\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:37.411844Z\", \"row_index\": 214, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1671.809434890747, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 36, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daens\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:39.554164Z\", \"row_index\": 215, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2138.319730758667, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Daens\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Titles are different (Daens vs Darling) and years are unrelated\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:41.787634Z\", \"row_index\": 216, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2229.4704914093018, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 41, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dad\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different titles and eras; no basis to link as same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:43.114581Z\", \"row_index\": 217, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1322.9472637176514, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 40, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dad\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles with different years; unlikely same real-world entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:45.010029Z\", \"row_index\": 218, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1891.4482593536377, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different and dates are far apart; no strong overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:46.350369Z\", \"row_index\": 219, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1336.338758468628, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different ('Dae' vs 'Darling') and no supporting data linking them\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:48.310465Z\", \"row_index\": 220, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1956.0966491699219, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly; unrelated works from different eras.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:50.494047Z\", \"row_index\": 221, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2179.579973220825, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 52, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title with one-year difference; uncertain without additional context, but could be different films or same with release date variation.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:53.049288Z\", \"row_index\": 222, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2552.243947982788, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with consecutive years could be different films; insufficient to confirm a single entity without additional attributes\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:55.194528Z\", \"row_index\": 223, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2141.240119934082, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dangerous\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Darling\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and no clear alias; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:56.982474Z\", \"row_index\": 224, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1784.9457263946533, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 43, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prince of Egypt\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to distinct productions (animated musical vs drama) with different years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:03:58.822725Z\", \"row_index\": 225, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1837.2509479522705, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 37, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prince of Tides\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release periods; unlikely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:00.281466Z\", \"row_index\": 226, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1455.7409286499023, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 43, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Profession of Arms\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different works by different titles and unrelated dates; no overlap suggesting same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:01.653445Z\", \"row_index\": 227, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1367.978811264038, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 571, \"output_tokens\": 41, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.78, \\\"explanation\\\": \\\"Same film title with one-year date difference; likely same movie.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:03.735043Z\", \"row_index\": 228, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2078.5982608795166, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 36, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pride of St. Louis\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different works with distinct titles and unrelated dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:05.259564Z\", \"row_index\": 229, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1521.5210914611816, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 36, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Pride of the Yankees\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and release periods; unrelated works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:06.530314Z\", \"row_index\": 230, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1267.751693725586, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 40, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Price of Victory\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no overlap in subject or release context\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:08.214556Z\", \"row_index\": 231, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1681.241750717163, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 39, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Prisoner of Zenda\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Prime of Miss Jean Brodie\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Different titles and non-overlapping data; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:09.685797Z\", \"row_index\": 232, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1467.2443866729736, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 50, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"As Good as It Gets\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"As Good As It Gets\\\", \\\"date\\\": \\\"1998-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Slight variation in title capitalization; likely same film but release years differ by 1 year; uncertainty remains.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:10.798072Z\", \"row_index\": 233, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1109.2720031738281, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 42, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different works with the same title across different years (likely different productions)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:12.158649Z\", \"row_index\": 234, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1357.5780391693115, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 43, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anna\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles are different and years are far apart; unlikely same real-world entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:13.732881Z\", \"row_index\": 235, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1570.2321529388428, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 49, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Annie\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are different; 1982 vs 1957 and different works (Annie vs Anastasia)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:15.611896Z\", \"row_index\": 236, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1876.0111331939697, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Anastasia\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.45, \\\"explanation\\\": \\\"Same title but different year; could be same film or different adaptation; uncertainty without additional metadata\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:17.012255Z\", \"row_index\": 237, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1396.3580131530762, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 41, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Face/Off\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different movie titles; both released in 1997 but unrelated titles\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:18.315743Z\", \"row_index\": 238, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1300.4887104034424, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 53, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different release years; could be same film with date inconsistency, but one-year difference is plausible; uncertain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:19.959403Z\", \"row_index\": 239, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1640.6595706939697, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fame\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly (Fame vs Fargo); unlikely same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:21.523473Z\", \"row_index\": 240, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1560.070514678955, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 39, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Faces\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no overlapping context or dates suggesting same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:23.654846Z\", \"row_index\": 241, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2127.376079559326, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Fanny\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Fargo\\\", \\\"date\\\": \\\"1997-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly; Fanny vs Fargo refer to different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:25.389044Z\", \"row_index\": 242, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1731.1997413635254, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 56, \"total_tokens\": 619, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Leaving Las Vegas\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Leaving Las Vegas\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title with 1-year date difference; likely same film released across years or festival/biography, but not enough to be certain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:27.238542Z\", \"row_index\": 243, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1846.5001583099365, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 44, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dead Man Walking\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dead Man Walking\\\", \\\"date\\\": \\\"1996-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different release years; could be sequel/remake but unlikely identical film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:29.293252Z\", \"row_index\": 244, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2051.7098903656006, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 51, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Forrest Gump\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Forest Gump\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.46, \\\"explanation\\\": \\\"Titles differ by one letter (Forrest vs Forest) though similar; years differ by 1, likely different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:31.004080Z\", \"row_index\": 245, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1707.8280448913574, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 41, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Nell\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles with unrelated release years; no indication of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:33.015969Z\", \"row_index\": 246, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2008.8849067687988, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 48, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.54, \\\"explanation\\\": \\\"Same title with consecutive years; could be remakes or related, but not enough to confirm same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:34.629454Z\", \"row_index\": 247, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1610.4860305786133, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 47, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Neighbours\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Network\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and genres likely; 1952 Neighbours vs 1977 Network are distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:36.118851Z\", \"row_index\": 248, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1485.3968620300293, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title but consecutive years suggest different works; uncertainty remains\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:37.676634Z\", \"row_index\": 249, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1554.7847747802734, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 47, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Blue Skies\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Blue Sky\\\", \\\"date\\\": \\\"1995-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Titles differ ('Blue Skies' vs 'Blue Sky'); different works and a large date gap\\\"})\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:39.828641Z\", \"row_index\": 250, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2149.007797241211, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 559, \"output_tokens\": 50, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title across consecutive years could be different works or the same with release date uncertainty; lacking additional distinguishing data.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:41.893263Z\", \"row_index\": 251, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2061.6257190704346, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 43, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pharaoh\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles; no strong overlap in subject or era to suggest same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:43.682666Z\", \"row_index\": 252, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1786.400556564331, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 45, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Phaedra\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Philadelphia\\\", \\\"date\\\": \\\"1994-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles differ significantly (Phaedra vs Philadelphia) and no corroborating data to link\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:45.086673Z\", \"row_index\": 253, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1401.0047912597656, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 45, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Partners\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles 'Partners' and 'Patton' are different; no corroborating date alignment\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:46.621197Z\", \"row_index\": 254, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1530.5204391479492, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Parenthood\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles and distinct films; no close relation inferred\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:48.630225Z\", \"row_index\": 255, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2006.0310363769531, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pathfinder\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no strong overlap; paths differ from Pathfinder to Patton\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:50.143620Z\", \"row_index\": 256, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1509.394884109497, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paradise\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.1, \\\"explanation\\\": \\\"Clearly different titles with different years; no basis to link.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:52.362313Z\", \"row_index\": 257, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2214.6923542022705, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Papillon\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.02, \\\"explanation\\\": \\\"Titles are distinct and refer to different works; years do not align.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:53.766483Z\", \"row_index\": 258, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1401.1728763580322, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 48, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same film title with adjacent release years likely the same movie; dataset variations can have +/-1 year differences\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:55.497543Z\", \"row_index\": 259, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1727.0593643188477, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 38, \"total_tokens\": 598, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Pan\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with unrelated subjects; no strong overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:56.709135Z\", \"row_index\": 260, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1208.587646484375, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paw\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Titles and subjects are unrelated; 'Paw' vs 'Patton' do not indicate same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:04:58.296257Z\", \"row_index\": 261, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1584.1248035430908, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 36, \"total_tokens\": 597, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paisan\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are completely different; unrelated works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:00.547070Z\", \"row_index\": 262, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2247.812032699585, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 36, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Paris--Underground\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Patton\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different works with unrelated titles and dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:02.711247Z\", \"row_index\": 263, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2161.1766815185547, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 51, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Titles identical but one-year difference could correspond to different releases; however likely same film but uncertain due to year discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:04.905246Z\", \"row_index\": 264, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2190.9987926483154, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 40, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Scent of a Woman\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different films with same title across many years; likely distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:06.776245Z\", \"row_index\": 265, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1867.0001029968262, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Howards End\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Howards End\\\", \\\"date\\\": \\\"1993-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film title with minor date difference (likely release year variation); high confidence of same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:08.654997Z\", \"row_index\": 266, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1874.753475189209, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 37, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different works with unrelated titles and dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:10.158628Z\", \"row_index\": 267, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1499.6304512023926, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 42, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.82, \\\"explanation\\\": \\\"Same title; one-year date difference likely due to release date metadata variability\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:12.032398Z\", \"row_index\": 268, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1869.769811630249, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 40, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sign of the Cross\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different titles and subjects; no clear overlap beyond generic religious motif\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:13.980891Z\", \"row_index\": 269, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1944.4921016693115, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 42, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sign of the Cross\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different films by title and era; no overlap in dates or \\u0441\\u044e\\u0436\\u0435\\u0442\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:15.709820Z\", \"row_index\": 270, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1725.9290218353271, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 571, \"output_tokens\": 46, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title; two-year difference likely represents different release years/editions of the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:17.423322Z\", \"row_index\": 271, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1709.5022201538086, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 42, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Sin of Madelon Claudet\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Silence of the Lambs\\\", \\\"date\\\": \\\"1992-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Completely different titles and unrelated works; no overlap in content or dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:19.325893Z\", \"row_index\": 272, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1899.5678424835205, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 45, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Different adaptations/films with the same title; dates differ by many years suggesting distinct works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:20.892204Z\", \"row_index\": 273, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1563.3113384246826, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 42, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cyrano de Bergerac\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Different release years imply distinct film productions; titles identical but separate works.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:22.437806Z\", \"row_index\": 274, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1541.6030883789062, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 44, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Reversal of Fortune\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Reversal of Fortune\\\", \\\"date\\\": \\\"1991-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.78, \\\"explanation\\\": \\\"Same title; adjacent years may reflect production/release differences but likely the same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:24.470376Z\", \"row_index\": 275, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2028.5677909851074, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ghost\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ghandi\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different titles and release years; no indication of being the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:26.457801Z\", \"row_index\": 276, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1984.4253063201904, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 39, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Ghostbusters\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Ghandi\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and years; no evidence of same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:28.670080Z\", \"row_index\": 277, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2209.2790603637695, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 53, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"My Left Foot\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"My Left Foot\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Identical title but different release year; possible same film with a different release date, but 1-year difference is uncommon.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:29.891526Z\", \"row_index\": 278, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1218.4467315673828, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 53, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Driving Miss Daisy\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Driving Miss Daisy\\\", \\\"date\\\": \\\"1990-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be different cuts or errors, but commonly treated as the same film if year differs slightly\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:36.439249Z\", \"row_index\": 279, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 6543.725967407227, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 45, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Rain Man\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Rain Man\\\", \\\"date\\\": \\\"1989-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film title with minor date difference; likely the same release year may vary by region\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:38.652596Z\", \"row_index\": 280, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2210.3445529937744, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunset\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles are clearly different; no evidence they refer to same work.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:40.296202Z\", \"row_index\": 281, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1640.608549118042, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Superman\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different titles and unrelated works; no evidence of same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:41.701791Z\", \"row_index\": 282, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1401.5905857086182, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunflower\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles; no strong evidence they refer to the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:43.205461Z\", \"row_index\": 283, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1500.6704330444336, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 39, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Summertime\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and eras; no strong overlap suggesting same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:44.937165Z\", \"row_index\": 284, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1727.7047634124756, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 56, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title appears in films from different years; 1941 vs 1942 could be different productions or releases, insufficient to confirm same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:47.196216Z\", \"row_index\": 285, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2255.9406757354736, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 40, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sundown\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles; no strong overlap in metadata to suggest same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:49.269218Z\", \"row_index\": 286, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2069.004535675049, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 560, \"output_tokens\": 41, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sunny\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and distinct films; no strong overlap on date or context\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:50.932570Z\", \"row_index\": 287, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1660.3515148162842, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 40, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Superman\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no strong linkage; unlikely same film or entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:52.335590Z\", \"row_index\": 288, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1399.0211486816406, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 42, \"total_tokens\": 603, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suez\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with different release years; no indication of being same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:54.048039Z\", \"row_index\": 289, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1708.4507942199707, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 38, \"total_tokens\": 599, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Suzy\\\", \\\"date\\\": \\\"1936-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Suspicion\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Titles differ significantly; unrelated works with different release years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:56.131853Z\", \"row_index\": 290, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2080.815315246582, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 46, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title and near years likely the same film released across consecutive years in different markets or editions\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:05:58.355828Z\", \"row_index\": 291, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2220.975875854492, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 57, \"total_tokens\": 624, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Children of a Lesser God\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Children of a Lesser God\\\", \\\"date\\\": \\\"1987-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different release years (1986 vs 1987) could indicate a sequel/edition; uncertain, but likely different production year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:00.851030Z\", \"row_index\": 292, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2492.2006130218506, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 58, \"total_tokens\": 627, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Same title but different release years; could be same film with date discrepancy or different versions. Unclear but leaning toward same film due to close years.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:02.507584Z\", \"row_index\": 293, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1653.5546779632568, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 37, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"King of the Zombies\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles and genres; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:03.869927Z\", \"row_index\": 294, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1359.3363761901855, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 39, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kings of the Turf\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kiss of the Spider Woman\\\", \\\"date\\\": \\\"1986-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Completely different titles and eras; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:05.478607Z\", \"row_index\": 295, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1605.6783199310303, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 39, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Angry Harvest\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different titles and release years; no plausible overlap.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:07.912219Z\", \"row_index\": 296, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2430.612564086914, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 52, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Annie Hall\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title but different release year; could be different editions or a typo, but 1-year difference suggests potential different film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:10.117194Z\", \"row_index\": 297, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2200.9739875793457, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 40, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Places in the Heart\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Places in the Heart\\\", \\\"date\\\": \\\"1985-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.82, \\\"explanation\\\": \\\"Same film title with one-year date difference likely the same movie\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:12.975202Z\", \"row_index\": 298, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2854.006767272949, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Tender Mercies\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Tender Mercies\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years could indicate sequel or different release; uncertainty but not enough to confirm same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:15.841908Z\", \"row_index\": 299, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2863.705635070801, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 44, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Terms of Endearment\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Terms of Endearment\\\", \\\"date\\\": \\\"1984-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.82, \\\"explanation\\\": \\\"Identical title with one-year date difference; likely same film with release year variance\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:17.784481Z\", \"row_index\": 300, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1939.5735263824463, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 50, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sophie's Choice\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Sophie\\ufffds Choice\\\", \\\"date\\\": \\\"1983-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Minor typographical variation in apostrophe character; same film though one-year difference could be a release year variance.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:20.065564Z\", \"row_index\": 301, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2277.0838737487793, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Diner\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.12, \\\"explanation\\\": \\\"Different titles with unrelated release years; no plausible match\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:21.732125Z\", \"row_index\": 302, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1663.5630130767822, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 43, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dillinger\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and non-overlapping data; no basis to link them.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:23.109473Z\", \"row_index\": 303, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1374.3491172790527, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 54, \"total_tokens\": 617, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Disraeli\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different release years; could be same film released in different markets or a misdated entry, but not enough to confirm\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:25.439250Z\", \"row_index\": 304, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2325.7761001586914, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 53, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"On Golden Pond\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"On Golden Pond\\\", \\\"date\\\": \\\"1982-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but 1-year difference; could be release variations, but more likely same film with minor date discrepancy; uncertain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:28.047807Z\", \"row_index\": 305, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2605.5562496185303, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 47, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Raging Bull\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Raging Bull\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.88, \\\"explanation\\\": \\\"Same title with near-identical data; 1-year difference likely same film with release date discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:30.267155Z\", \"row_index\": 306, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2216.3467407226562, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 56, \"total_tokens\": 621, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coal Miner's Daughter\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coal Miner\\ufffds Daughter\\\", \\\"date\\\": \\\"1981-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Titles are essentially the same, with a typographic apostrophe variation; dates differ by 1 year, suggesting the same work with slight discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:32.102230Z\", \"row_index\": 307, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1831.078290939331, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 47, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kramer vs. Kramer\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kramer vs. Kramer\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title with minor date difference; likely the same film released around 1979\\u20131980\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:34.441404Z\", \"row_index\": 308, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2336.18426322937, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 52, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Norma Rae\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Norma Rae\\\", \\\"date\\\": \\\"1980-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but 1-year difference; likely same film but could be re-release or award year mismatch. Uncertain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:36.172420Z\", \"row_index\": 309, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1728.0151844024658, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 63, \"total_tokens\": 624, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Coming Home\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Coming Home\\\", \\\"date\\\": \\\"1979-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with consecutive years; could be different films or a misdated record. However, 1978 vs 1979 suggests potential different film, not confidently the same.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:37.993791Z\", \"row_index\": 310, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1817.3696994781494, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 49, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Goodbye Girl\\\", \\\"date\\\": \\\"1977-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Goodbye Girl\\\", \\\"date\\\": \\\"1978-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Same title but different release years suggest different films; however close in time makes coincidence possible but not definitive.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:39.840712Z\", \"row_index\": 311, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1843.8100814819336, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 577, \"output_tokens\": 54, \"total_tokens\": 631, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"One Flew over the Cuckoo's Nest\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"One Flew Over The Cuckoo's Nes\\\", \\\"date\\\": \\\"1976-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles are highly similar but have a minor misspelling; dates differ by 1 year suggesting potential same film but uncertainty remains.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:41.767480Z\", \"row_index\": 312, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1922.7681159973145, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 46, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Harry and Tonto\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Harry and Tonto\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title with 1-year date difference likely the same film (Harry and Tonto)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:44.518668Z\", \"row_index\": 313, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2746.180772781372, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 572, \"output_tokens\": 84, \"total_tokens\": 656, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Alice Doesn't Live Here Anymore\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Alice Doesn\\ufffdt live Here Anymor\\\", \\\"date\\\": \\\"1975-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.45, \\\"explanation\\\": \\\"Titles are nearly identical but contain a typographical/apostrophe difference ('Doesn\\u2019t' vs 'Doesn\\u2019t' with a non-ASCII character in second). Date differs by 1 year; potential data quality issues suggest likely same work, but ambiguity due to character encoding.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:45.747202Z\", \"row_index\": 314, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1225.5327701568604, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 44, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Save the Tiger\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Save the Tiger\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same movie with very close release years; likely the same entity with minor date variation\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:47.254634Z\", \"row_index\": 315, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1504.4317245483398, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 43, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Touch of Class\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Touch of Class\\\", \\\"date\\\": \\\"1974-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Titles match but year difference may indicate different release; insufficient to confirm same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:49.232946Z\", \"row_index\": 316, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1974.3061065673828, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Robin Hood\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Titles refer to different works with different release years; unlikely same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:51.765298Z\", \"row_index\": 317, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2528.3515453338623, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 54, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be the same film with date variability, but likely different release year records; uncertainty remains.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:53.894433Z\", \"row_index\": 318, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2126.1353492736816, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 38, \"total_tokens\": 600, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Robin Hoodlum\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Roman Holiday\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Clearly different titles and eras; no plausible entity overlap\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:55.874075Z\", \"row_index\": 319, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1976.6426086425781, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 47, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release year; could be a sequel or misdate, but not identical records\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:57.490907Z\", \"row_index\": 320, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1612.8313541412354, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 564, \"output_tokens\": 37, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Go-Between\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.05, \\\"explanation\\\": \\\"Clearly different works with distinct titles and release years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:06:59.575337Z\", \"row_index\": 321, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2081.430435180664, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 42, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Goddess\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Godfather\\\", \\\"date\\\": \\\"1973-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles with no strong overlap and different years; unlikely same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:01.273819Z\", \"row_index\": 322, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1695.4824924468994, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The French Connection\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The French Connection\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Different release years for same title but could be re-release; not enough to confirm same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:03.415153Z\", \"row_index\": 323, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2137.3350620269775, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 47, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Klute\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Klute\\\", \\\"date\\\": \\\"1972-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.88, \\\"explanation\\\": \\\"Same film title with one-year difference; likely identical entity (Klute, 1971).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:05.153658Z\", \"row_index\": 324, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1735.5051040649414, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 42, \"total_tokens\": 605, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Women in Love\\\", \\\"date\\\": \\\"1970-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Women In Love\\\", \\\"date\\\": \\\"1971-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film title with minor date difference due to production year vs release date\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:07.514471Z\", \"row_index\": 325, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2357.813835144043, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 45, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.2, \\\"explanation\\\": \\\"Different film releases; 1969 vs 1940 suggest separate productions despite same title\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:09.067395Z\", \"row_index\": 326, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1549.9241352081299, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 46, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same title and near in release years; likely same film released in different regions or re-release\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:10.577872Z\", \"row_index\": 327, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1507.4775218963623, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 48, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Lion in Winter\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Lion in Winter\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but one-year difference could be same film released across regions; however there is historical ambiguity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:11.956811Z\", \"row_index\": 328, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1375.93674659729, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 51, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Funny Girl\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Funny Girl\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different release year; could be a re-release or sequel, but unlikely to be the same exact film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:14.098078Z\", \"row_index\": 329, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2138.267755508423, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 50, \"total_tokens\": 619, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"In the Heat of the Night\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"In the Heat of the Night\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title with consecutive years; could be a sequel/remake but not identical release year suggests different works or editions\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:16.234417Z\", \"row_index\": 330, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2132.3392391204834, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 62, \"total_tokens\": 631, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Guess Who's Coming to Dinner\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Guess Who\\ufffds Coming to Dinner\\\", \\\"date\\\": \\\"1968-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Titles are nearly identical but apostrophe characters differ (ASCII vs typographic) and 1-year date difference could indicate a closely related release; uncertainty about exact same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:18.350669Z\", \"row_index\": 331, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2112.2512817382812, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 572, \"output_tokens\": 64, \"total_tokens\": 636, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Who's Afraid of Virginia Woolf?\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Who\\ufffds Afraid of Virginia Woolf\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Titles are very similar with a minor typographic difference (curly apostrophe vs ASCII) and a one-year date difference; likely same work but metadata variance reasons introduce some uncertainty.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:19.573428Z\", \"row_index\": 332, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1219.7599411010742, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 51, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Man for All Seasons\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Man for All Seasons\\\", \\\"date\\\": \\\"1967-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release year; could be same film released in different markets or a variant, but uncertainty remains.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:21.040059Z\", \"row_index\": 333, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1462.6309871673584, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 39, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Cat Ballou\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Cat Ballou\\\", \\\"date\\\": \\\"1966-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film with identical title despite 1-year date difference\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:22.378545Z\", \"row_index\": 334, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1334.4860076904297, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 38, \"total_tokens\": 601, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"My Fair Lady\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"My Fair Lady\\\", \\\"date\\\": \\\"1965-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same production (film) with minor date discrepancy.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:23.867705Z\", \"row_index\": 335, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1485.1624965667725, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 48, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Lilies of the Field\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Lilies of the Field\\\", \\\"date\\\": \\\"1964-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be different films with same title but likely a different production year\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:25.602696Z\", \"row_index\": 336, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1730.9906482696533, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 40, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"To Kill a Mockingbird\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"To Kill a Mockingbird\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film title with one-year date difference likely the same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:26.772228Z\", \"row_index\": 337, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1166.5325164794922, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 55, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Miracle Worker\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Miracle Worker\\\", \\\"date\\\": \\\"1963-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"The Miracle Worker titles are identical but release years differ by 1 year; could be same film released in different markets, but uncertainty.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:28.623370Z\", \"row_index\": 338, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1848.1390476226807, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 566, \"output_tokens\": 48, \"total_tokens\": 614, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Walk on the Wild Side\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Dissimilar titles with no obvious aliasing and large date gap; unlikely to refer to same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:30.675640Z\", \"row_index\": 339, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2048.267364501953, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 56, \"total_tokens\": 621, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Watch on the Rhine\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but 1-year difference; could be same work but uncertain due to potential adaptations or editions. However, dates differ by year.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:32.665613Z\", \"row_index\": 340, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1986.9749546051025, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 58, \"total_tokens\": 628, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Judgment at Nuremberg\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Judgment at Nuremburg\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.58, \\\"explanation\\\": \\\"Similar title with minor spelling variance ('Nuremberg' vs 'Nuremburg'), close dates but not exact; likely same film with alternate spelling\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:34.760164Z\", \"row_index\": 341, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2089.5488262176514, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 52, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Two Women\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Two Women\\\", \\\"date\\\": \\\"1962-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.4, \\\"explanation\\\": \\\"Same title but different release year; could be same film with date discrepancy but 1-year difference is plausible; uncertain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:36.933254Z\", \"row_index\": 342, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2170.0897216796875, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 54, \"total_tokens\": 619, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Elmer Gantry\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Elmer Gantry\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Different release year by 1 year may indicate same film edition? Unable to confirm; cautious approach yields low confidence but not definitive.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:38.644653Z\", \"row_index\": 343, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1708.3959579467773, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 78, \"total_tokens\": 643, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Butterfield 8\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Butterfield 8\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Close release years but 1960 vs 1961 could be same film with release year variance; however Butterfield 8 is a known 1960 film; 1961 likely different release or misdated. Uncertain but not confidently same.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:40.743928Z\", \"row_index\": 344, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2095.2751636505127, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"High Note\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.15, \\\"explanation\\\": \\\"Different titles (High Note vs High Noon) with different years; no strong overlap to suggest same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:42.366721Z\", \"row_index\": 345, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1619.793176651001, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 41, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"High Noon\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same movie title with minor date discrepancy; likely the same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:43.671898Z\", \"row_index\": 346, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1301.177978515625, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 44, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Room at the Top\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Room at the Top\\\", \\\"date\\\": \\\"1960-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same title with one-year date difference; could be different release years but same work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:44.974529Z\", \"row_index\": 347, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1298.6321449279785, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Separate Tables\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Separate Tables\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.52, \\\"explanation\\\": \\\"Same title but consecutive years; could be same film with alternate release dates or different editions, but uncertainty remains\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:46.213821Z\", \"row_index\": 348, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1235.292911529541, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 41, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"I Want to Live!\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"I Want to Live!\\\", \\\"date\\\": \\\"1959-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same movie title with one-year date difference; likely the same entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:47.673630Z\", \"row_index\": 349, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1455.8088779449463, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 571, \"output_tokens\": 60, \"total_tokens\": 631, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Bridge on the River Kwai\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Bridge On The River Kwai\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.42, \\\"explanation\\\": \\\"Titles differ in capitalization; potential same film but one-year difference with misspelling 'On The' vs 'on the' could indicate variant; insufficient certainty.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:49.073623Z\", \"row_index\": 350, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1395.9927558898926, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 40, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Brave One\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Bridge On The River Kwai\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.18, \\\"explanation\\\": \\\"Different titles and unrelated release years; no strong overlap in entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:51.256902Z\", \"row_index\": 351, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2180.278539657593, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 40, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Three Faces of Eve\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Three Faces of Eve\\\", \\\"date\\\": \\\"1958-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Identical title with one-year date discrepancy, likely same film\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:52.740303Z\", \"row_index\": 352, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1479.402780532837, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 45, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The King and I\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The King and I\\\", \\\"date\\\": \\\"1957-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.82, \\\"explanation\\\": \\\"Same title; likely the same film released in adjacent years due to production or release differences\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:54.124226Z\", \"row_index\": 353, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1380.9194564819336, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 43, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Rose Tattoo\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Rose Tattoo\\\", \\\"date\\\": \\\"1956-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but consecutive years could indicate different productions; uncertain but likely different works\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:55.501536Z\", \"row_index\": 354, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1374.3071556091309, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"On the Waterfront\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"On The Waterfront\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.62, \\\"explanation\\\": \\\"Same film with minor title capitalization/date discrepancy; likely the same entity (On the Waterfront, 1954).\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:56.632571Z\", \"row_index\": 355, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1128.0343532562256, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 43, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Country Girl\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Country Girl\\\", \\\"date\\\": \\\"1955-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.75, \\\"explanation\\\": \\\"Same film title with consecutive years; likely the same movie released across different years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:58.015659Z\", \"row_index\": 356, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1379.0841102600098, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 50, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Stalag 17\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Stalag 17\\\", \\\"date\\\": \\\"1954-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with one-year difference could be sequel/remake; without additional attributes, uncertain but often same film.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:07:59.703270Z\", \"row_index\": 357, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1683.610439300537, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 44, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Come Back, Little Sheba\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Come Back, Little Sheba\\\", \\\"date\\\": \\\"1953-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film title with consecutive years; likely same movie despite 1-year date difference\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:01.690505Z\", \"row_index\": 358, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1984.2357635498047, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The African Queen\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The African Queen\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but one-year date difference could be separate release years; however likely same film with staggered release dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:03.867231Z\", \"row_index\": 359, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2173.0761528015137, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 40, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Streetcar Named Desire\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Streetcar Named Desire\\\", \\\"date\\\": \\\"1952-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same title; one-year difference likely due to release date variance\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:05.212680Z\", \"row_index\": 360, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1341.4478302001953, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 48, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Born Yesterday\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Born Yesterday\\\", \\\"date\\\": \\\"1951-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but consecutive years suggest different film editions; however, could be remakes or a re-release\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:07.729845Z\", \"row_index\": 361, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2513.1635665893555, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 51, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"All the King's Men\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"All the King's Men\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.65, \\\"explanation\\\": \\\"Same title with close release years; may refer to different film versions or a remake, but likely the same core work\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:09.920690Z\", \"row_index\": 362, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2186.842679977417, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 81, \"total_tokens\": 644, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Heiress\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Heiress\\\", \\\"date\\\": \\\"1950-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title with adjacent years could be the same version? Further check: 1949 vs 1950 may be re-release or different adaptation; uncertainty remains but likely same film with minor release variations, hence cautious false? The decision: moderate likelihood but not definitive.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:11.358592Z\", \"row_index\": 363, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1433.9017868041992, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 63, \"total_tokens\": 626, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Johnny Belinda\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Johnny Belinda\\\", \\\"date\\\": \\\"1949-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with consecutive years; could be the same film release year varies by source, but a 1-year difference makes it ambiguous. Likely same entity but not certain.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:12.695064Z\", \"row_index\": 364, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1333.4720134735107, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 45, \"total_tokens\": 608, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Double Life\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Double Life\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film title with consecutive years likely the same movie release variant; minor date difference.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:14.805467Z\", \"row_index\": 365, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2106.402635574341, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 50, \"total_tokens\": 615, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Farmer's Daughter\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Farmer\\ufffds Daughter\\\", \\\"date\\\": \\\"1948-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Titles essentially identical with a minor character encoding difference; dates differ by 1 year, could be same film releases\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:17.061484Z\", \"row_index\": 366, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2252.016544342041, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 575, \"output_tokens\": 76, \"total_tokens\": 651, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Mouse\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.45, \\\"explanation\\\": \\\"Similar titles but different works (Dr. Jekyll and Mr. Mouse appears to be a parody/short, vs Dr. Jekyll and Mr. Hyde classic) with different release years; uncertainty but not confident they are the same\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:18.688777Z\", \"row_index\": 367, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1624.2930889129639, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 575, \"output_tokens\": 70, \"total_tokens\": 645, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.45, \\\"explanation\\\": \\\"Same title but different release years could refer to different adaptations; the 1931/1941 Jekyll and Hyde films exist, but 1941 and 1933 suggest distinct productions, uncertain alignment.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:20.345498Z\", \"row_index\": 368, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1652.7209281921387, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 575, \"output_tokens\": 45, \"total_tokens\": 620, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Dr. Jekyll and Mr. Hyde\\\", \\\"date\\\": \\\"1933-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same title, different release year likely same film with typical two-year production/post-release variation\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:22.692256Z\", \"row_index\": 369, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2343.759298324585, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 568, \"output_tokens\": 39, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened on Fifth Avenue\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Different titles; similar words but not the same film title\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:24.724187Z\", \"row_index\": 370, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2028.9311408996582, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 567, \"output_tokens\": 43, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.93, \\\"explanation\\\": \\\"Same movie title with minor date discrepancy (1934 vs 1935)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:26.225844Z\", \"row_index\": 371, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1497.6577758789062, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 47, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Best Years of Our Lives\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Best Years of Our Lives\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film with near-identical title; 1946 vs 1947 likely release year discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:28.335662Z\", \"row_index\": 372, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2105.6294441223145, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 44, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"To Each His Own\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"To Each His Own\\\", \\\"date\\\": \\\"1947-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same title with close release years; likely the same film with a one-year discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:29.924241Z\", \"row_index\": 373, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1584.580421447754, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 53, \"total_tokens\": 616, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Lost Weekend\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Lost Weekend\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with one-year difference could indicate same film with release date variation; however the canonical release year is 1945.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:31.788054Z\", \"row_index\": 374, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1859.8136901855469, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 48, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mildred Pierce\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mildred Pierce\\\", \\\"date\\\": \\\"1946-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same film title with a one-year date difference likely same entity (pre-release vs release year variance)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:33.035138Z\", \"row_index\": 375, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1243.088722229004, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 49, \"total_tokens\": 612, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Going My Way\\\", \\\"date\\\": \\\"1944-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Going My Way\\\", \\\"date\\\": \\\"1945-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.85, \\\"explanation\\\": \\\"Same movie title with consecutive years; likely the same film (The film won Best Picture 1944)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:34.500495Z\", \"row_index\": 376, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1461.3573551177979, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 571, \"output_tokens\": 47, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Yankee Doodle Dandy\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Yankee Doodle Dandy\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.6, \\\"explanation\\\": \\\"Same title with consecutive years but could be different releases; insufficient to confirm same entity without more data\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:36.443478Z\", \"row_index\": 377, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1939.9828910827637, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 44, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Mrs. Miniver\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Mrs. Miniver\\\", \\\"date\\\": \\\"1943-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Two consecutive years suggest different releases or editions; title identical but uncertain beyond year difference\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:38.066160Z\", \"row_index\": 378, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1618.5283660888672, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 41, \"total_tokens\": 604, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Sergeant York\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Sergeant York\\\", \\\"date\\\": \\\"1942-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film title with near-year release; likely the same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:39.649030Z\", \"row_index\": 379, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1579.869270324707, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 66, \"total_tokens\": 629, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Philadelphia Story\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Philadelphia Story\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but one-year difference likely same film; however data ambiguity due to possible remake? Yet widely known 1940 film; 1941 date likely error. Treat as same entity.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:41.100198Z\", \"row_index\": 380, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1447.1690654754639, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 64, \"total_tokens\": 629, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Kitty Foyle\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Kitty Foyle\\\", \\\"date\\\": \\\"1941-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but year differs by 1; could be the same film released near end of year, but 1940 vs 1941 suggests different production years; uncertain scope.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:42.410474Z\", \"row_index\": 381, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1306.2753677368164, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 562, \"output_tokens\": 44, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boom Town\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": \\\"false\\\", \\\"score\\\": 0.28, \\\"explanation\\\": \\\"Different titles with minimal similarity; distinct films (Boom Town vs Boys Town)\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:44.161107Z\", \"row_index\": 382, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1746.6316223144531, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 44, \"total_tokens\": 607, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Boys Town\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.82, \\\"explanation\\\": \\\"Same film title with consecutive release years; likely the same movie across different release dates\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:45.468469Z\", \"row_index\": 383, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1303.3623695373535, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 41, \"total_tokens\": 606, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Gone with the Wind\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Gone With the Wind\\\", \\\"date\\\": \\\"1940-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.92, \\\"explanation\\\": \\\"Same film with minor title casing difference and a one-year date discrepancy\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:46.985300Z\", \"row_index\": 384, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1512.829303741455, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 570, \"output_tokens\": 39, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Lives of Elizabeth and Essex\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.35, \\\"explanation\\\": \\\"Different films with distinct titles and characters; years differ significantly\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:48.637593Z\", \"row_index\": 385, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1648.2911109924316, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 571, \"output_tokens\": 39, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Life of the Gannets\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.25, \\\"explanation\\\": \\\"Different films with distinct titles and likely different subjects/years\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:50.715178Z\", \"row_index\": 386, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 2073.585033416748, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 569, \"output_tokens\": 52, \"total_tokens\": 621, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Private Life of Henry VIII\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.78, \\\"explanation\\\": \\\"Same title with two-year difference likely referring to different release years of The Private Life of Henry VIII; common in film records\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:52.690209Z\", \"row_index\": 387, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1971.0302352905273, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Jezebel\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Jezebel\\\", \\\"date\\\": \\\"1939-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title with consecutive years could be remakes or different films; insufficient to confirm a single entity without more data\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:54.100107Z\", \"row_index\": 388, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1405.8947563171387, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 565, \"output_tokens\": 46, \"total_tokens\": 611, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Captains Courageous\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Captains Courageous\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.68, \\\"explanation\\\": \\\"Same film with very close release years; potential re-release or production ambiguity but likely same movie\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:55.374253Z\", \"row_index\": 389, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1270.1456546783447, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 46, \"total_tokens\": 609, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Good Earth\\\", \\\"date\\\": \\\"1937-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Good Earth\\\", \\\"date\\\": \\\"1938-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but consecutive years could indicate a remake; insufficient to confirm same entity without additional metadata\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:57.249045Z\", \"row_index\": 390, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1870.795726776123, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 561, \"output_tokens\": 49, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Morning Glory\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Morning Glory\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.38, \\\"explanation\\\": \\\"Same title but two different release years; could be different films or remakes, insufficient to confirm identical entity\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:08:59.223664Z\", \"row_index\": 391, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1970.6177711486816, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 62, \"total_tokens\": 625, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"A Free Soul\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"A Free Soul\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; could be same film with date inconsistency, but two-year gap suggests possible different versions or misdated data; uncertainty keeps at moderate.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:09:00.607488Z\", \"row_index\": 392, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1379.82177734375, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 55, \"total_tokens\": 618, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Min and Bill\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Min and Bill\\\", \\\"date\\\": \\\"1932-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title used for related films across years, but two different release years suggest distinct films; ambiguity but likely related remakes or sequels\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:09:02.027889Z\", \"row_index\": 393, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1416.4009094238281, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 47, \"total_tokens\": 610, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"The Divorcee\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"The Divorcee\\\", \\\"date\\\": \\\"1931-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years; potential remakes/sequels exist but likely distinct films.\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:09:03.286131Z\", \"row_index\": 394, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1253.2427310943604, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 50, \"total_tokens\": 613, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"In Old Arizona\\\", \\\"date\\\": \\\"1928-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"In Old Arizona\\\", \\\"date\\\": \\\"1930-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": false, \\\"score\\\": 0.55, \\\"explanation\\\": \\\"Same title but different release years suggest distinct films; however could be early/alternate editions, but likely different productions\\\"}\"}\n", "[INFO ] httpx - HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "[INFO ] PyDI.utils.llm - LLM call: {\"timestamp\": \"2025-10-22T10:09:05.046397Z\", \"row_index\": 395, \"attempt\": 0, \"provider_class\": \"ChatOpenAI\", \"model\": \"gpt-5-nano\", \"duration_ms\": 1756.2661170959473, \"temperature\": null, \"max_tokens\": null, \"usage\": {\"input_tokens\": 563, \"output_tokens\": 39, \"total_tokens\": 602, \"input_token_details\": {\"audio\": 0, \"cache_read\": 0}, \"output_token_details\": {\"audio\": 0, \"reasoning\": 0}}, \"request_messages\": [{\"type\": \"system\", \"content\": \"You are an expert entity resolver. Your task is to decide if two records refer to the same real-world entity.\\n\\nAnalyze the provided records carefully and return your decision as strict JSON in this format:\\n{\\\"match\\\": true|false, \\\"score\\\": , \\\"explanation\\\": \\\"\\\"}\\n\\nGuidelines:\\n- score should reflect your confidence (1.0 = definitely same entity, 0.0 = definitely different)\\n- match should be true if score >= 0.5, false otherwise \\n- explanation should be concise (1-2 sentences)\\n- Consider variations in naming, formatting, abbreviations, and data quality\\n- Respond with ONLY the JSON object and nothing else.\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 2-year date discrepancy'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1934-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"It Happened One Night\\\", \\\"date\\\": \\\"1935-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'true', 'score': 0.95, 'explanation': 'Same movie with identical title despite 1-year date difference'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1969-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Goodbye, Mr. Chips\\\", \\\"date\\\": \\\"1940-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.1, 'explanation': 'Different movie versions despite identical title - 29-year gap indicates remake'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"Back Street\\\", \\\"date\\\": \\\"1961-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"Wall Street\\\", \\\"date\\\": \\\"1988-01-01\\\"}\"}, {\"type\": \"ai\", \"content\": \"{'match': 'false', 'score': 0.2, 'explanation': 'Different movies despite both having Street - Back Street vs Wall Street'}\"}, {\"type\": \"human\", \"content\": \"Left record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1927-01-01\\\"}\\nRight record: {\\\"title\\\": \\\"7th Heaven\\\", \\\"date\\\": \\\"1929-01-01\\\"}\\n\\nReturn JSON matching the schema described above.\"}], \"response_text_preview\": \"{\\\"match\\\": true, \\\"score\\\": 0.95, \\\"explanation\\\": \\\"Same movie with identical title despite 2-year date difference\\\"}\"}\n", "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 46\n", "[INFO ] root - True Negatives: 100\n", "[INFO ] root - False Positives: 0\n", "[INFO ] root - False Negatives: 4\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.973\n", "[INFO ] root - Precision: 1.000\n", "[INFO ] root - Recall: 0.920\n", "[INFO ] root - F1-Score: 0.958\n" ] } ], "source": [ "# Run LLM-based matching with few-shot examples\n", "print(\"Running LLM-based matching with few-shot examples...\\n\")\n", "print(\"(This may take several minutes depending on the number of candidates)\\n\")\n", "\n", "correspondences_llm_fewshot = llm_matcher.match(\n", " df_left=df_academy,\n", " df_right=df_actors,\n", " candidates=blocker_standard,\n", " chat_model=chat_model,\n", " fields=attributes_for_llm,\n", " id_column='id',\n", " few_shots=few_shot_examples,\n", " out_dir=OUTPUT_DIR / \"llm_fewshot\",\n", " debug=True\n", ")\n", "\n", "\n", "# Evaluate the few-shot results\n", "eval_results_fewshot = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=correspondences_llm_fewshot,\n", " test_pairs=df_test,\n", " out_dir=OUTPUT_DIR / \"llm_fewshot\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Perfect! We can see a strong improvement when using few-shot examples, even giving us the best result yet! Let's verify on the test set:" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[INFO ] root - Confusion Matrix:\n", "[INFO ] root - True Positives: 46\n", "[INFO ] root - True Negatives: 100\n", "[INFO ] root - False Positives: 0\n", "[INFO ] root - False Negatives: 4\n", "[INFO ] root - Performance Metrics:\n", "[INFO ] root - Accuracy: 0.973\n", "[INFO ] root - Precision: 1.000\n", "[INFO ] root - Recall: 0.920\n", "[INFO ] root - F1-Score: 0.958\n" ] } ], "source": [ "eval_results = EntityMatchingEvaluator.evaluate_matching(\n", " correspondences=correspondences_llm_fewshot,\n", " test_pairs=df_test,\n", " out_dir=debug_output_dir\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's save our generated correspondences, so we can later use them in data fusion. You can either save them as pickle files or use the standard pandas `write_csv` function." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "correspondences_output_dir = OUTPUT_DIR / \"correspondences\"\n", "correspondences_output_dir.mkdir(parents=True, exist_ok=True)\n", "\n", "correspondences_llm_fewshot.to_pickle(f\"{OUTPUT_DIR}/correspondences/correspondences_llm_fewshot.pkl\")\n", "\n", "correspondences_llm_fewshot.to_csv(f\"{OUTPUT_DIR}/correspondences/correspondences_llm_fewshot.csv\", index=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's it for identity resolution! Now go ahead, create your evaluation sets and match your datasets!\n", "\n", "Keep in mind that you have to perform identity resolution at least twice:\n", "\n", "If you have datasets A, B, C, you need to create correspondences between at least two pairs of datasets, e.g. A-B and B-C. Think about which dataset should be the \"connector\" for your use case. Often it is the best choice to choose the largest dataset." ] } ], "metadata": { "kernelspec": { "display_name": "pydi-dev", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.11" } }, "nbformat": 4, "nbformat_minor": 4 }