cognee/notebooks/ontology_demo.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "25cf0a40e669a70",
"metadata": {},
"source": [
"# Understanding Ontologies with Cognee\n",
"\n",
"This notebook demonstrates how to work with ontologies in scientific research using the Cognee framework. We'll explore how ontologies can enhance our understanding and querying of scientific papers.\n",
"\n",
"## What is an Ontology?\n",
"\n",
"An ontology is a formal representation of knowledge that defines:\n",
"- Concepts within a domain\n",
"- Relationships between concepts\n",
"- Properties and attributes\n",
"- Rules and constraints\n",
"\n",
"Key terms:\n",
"- **Classes**: Categories or types (e.g., Disease, Symptom)\n",
"- **Instances**: Specific examples of classes (e.g., Type 2 Diabetes)\n",
"- **Properties**: Relationships between classes/instances (e.g., hasSymptom)\n",
"- **Axioms**: Logical statements defining relationships"
]
},
{
"cell_type": "markdown",
"id": "441248da37f2b901",
"metadata": {},
"source": [
"## Setup\n",
"\n",
"First, let's install the required packages and set up our environment:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "8cf7ba29f9a150af",
"metadata": {
"ExecuteTime": {
"end_time": "2025-03-26T16:17:55.937140Z",
"start_time": "2025-03-26T16:17:55.908542Z"
}
},
"outputs": [],
"source": [
"# Install required package\n",
"# !pip install cognee"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d825d126b3a0ec26",
"metadata": {
"ExecuteTime": {
"end_time": "2025-03-26T16:18:09.382400Z",
"start_time": "2025-03-26T16:18:09.342349Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:37:14.988241\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDeleted old log file: /Users/daulet/Desktop/dev/cognee-claude/logs/2025-08-26_12-45-20.log\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"/Users/daulet/Desktop/dev/cognee-claude/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n",
"\n",
"\u001b[2m2025-08-27T13:37:16.002327\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mLogging initialized \u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m \u001b[36mcognee_version\u001b[0m=\u001b[35m0.2.4-local\u001b[0m \u001b[36mdatabase_path\u001b[0m=\u001b[35m/Users/daulet/Desktop/dev/cognee-claude/cognee/.cognee_system/databases\u001b[0m \u001b[36mgraph_database_name\u001b[0m=\u001b[35m\u001b[0m \u001b[36mos_info\u001b[0m=\u001b[35m'Darwin 24.5.0 (Darwin Kernel Version 24.5.0: Tue Apr 22 19:54:43 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T8132)'\u001b[0m \u001b[36mpython_version\u001b[0m=\u001b[35m3.12.7\u001b[0m \u001b[36mrelational_config\u001b[0m=\u001b[35mcognee_db\u001b[0m \u001b[36mstructlog_version\u001b[0m=\u001b[35m25.4.0\u001b[0m \u001b[36mvector_config\u001b[0m=\u001b[35mlancedb\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:16.003141\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDatabase storage: /Users/daulet/Desktop/dev/cognee-claude/cognee/.cognee_system/databases\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n"
]
}
],
"source": [
"# Import required libraries\n",
"import os\n",
"import cognee\n",
"from cognee.shared.logging_utils import get_logger\n",
"from cognee.api.v1.search import SearchType\n",
"\n",
"logger = get_logger()\n",
"\n",
"# Set up OpenAI API key (required for Cognee's LLM functionality)\n",
"if \"LLM_API_KEY\" not in os.environ:\n",
" os.environ[\"LLM_API_KEY\"] = \"your-api-key-here\" # Replace with your API key"
]
},
{
"cell_type": "markdown",
"id": "6af350837e86b7a1",
"metadata": {},
"source": [
"## Creating the Pipeline\n",
"\n",
"Let's create a pipeline that will:\n",
"1. Clean existing data\n",
"2. Process scientific papers\n",
"3. Apply ontological knowledge"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4d0e4a58e4207a7d",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T17:12:54.006718Z",
"start_time": "2025-04-09T17:12:53.992906Z"
}
},
"outputs": [],
"source": [
"async def run_pipeline(ontology_path=None):\n",
" # Clean existing data\n",
" await cognee.prune.prune_data()\n",
" await cognee.prune.prune_system(metadata=True)\n",
" \n",
" # Set up path to scientific papers\n",
" scientific_papers_dir = os.path.join(\n",
" os.path.dirname(os.path.dirname(os.path.abspath(\".\"))), \n",
" \"cognee\",\n",
" \"examples\",\n",
" \"data\", \n",
" \"scientific_papers/\"\n",
" )\n",
" \n",
" # Add papers to the system\n",
" await cognee.add(scientific_papers_dir)\n",
" \n",
" # Cognify with optional ontology\n",
" return await cognee.cognify(ontology_file_path=ontology_path)\n",
"\n",
"async def query_pipeline(questions):\n",
" answers = []\n",
" for question in questions:\n",
" search_results = await cognee.search(\n",
" query_type=SearchType.GRAPH_COMPLETION,\n",
" query_text=question,\n",
" )\n",
" answers.append(search_results)\n",
" return answers"
]
},
{
"cell_type": "markdown",
"id": "c87c21a75d6f4d79",
"metadata": {},
"source": [
"## Running the Demo\n",
"\n",
"Let's test our system with some medical questions, comparing results with and without ontological knowledge:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "1363772d2b48f5c0",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T17:14:31.818452Z",
"start_time": "2025-04-09T17:12:55.491598Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"--- Results WITH ontology ---\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:37:26.484857\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDeleted Kuzu database files at /Users/daulet/Desktop/dev/cognee-claude/cognee/.cognee_system/databases/cognee_graph_kuzu\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:26.852005\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDatabase deleted successfully.\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[1mLangfuse client is disabled since no public_key was provided as a parameter or environment variable 'LANGFUSE_PUBLIC_KEY'. See our docs: https://langfuse.com/docs/sdk/python/low-level-sdk#initialize-client\u001b[0m\n",
"\u001b[92m14:37:27 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"User af34782a-1cf6-4632-8a3a-de25f57af415 has registered.\n"
]
},
{
"name": "stderr",
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"\n",
"\u001b[1mEmbeddingRateLimiter initialized: enabled=False, requests_limit=60, interval_seconds=60\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:31.914752\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `49b3ca10-a420-5f3d-b7c1-88e5074b4697`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.111670\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.294058\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.517354\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mRegistered loader: pypdf_loader\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.LoaderEngine\u001b[0m]\u001b[0m\n",
"\n",
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"\n",
"\u001b[2m2025-08-27T13:37:32.519003\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mRegistered loader: image_loader\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.LoaderEngine\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.519414\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mRegistered loader: audio_loader\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.LoaderEngine\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.519853\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mRegistered loader: unstructured_loader\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.LoaderEngine\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.522891\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mReading PDF: /Users/daulet/Desktop/dev/cognee/examples/data/scientific_papers/nutrients-13-01241.pdf\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.external.pypdf_loader\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.656457\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:32.817839\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.014369\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `49b3ca10-a420-5f3d-b7c1-88e5074b4697`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.174721\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `49b3ca10-a420-5f3d-b7c1-88e5074b4697`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.343251\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.541023\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.718918\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mReading PDF: /Users/daulet/Desktop/dev/cognee/examples/data/scientific_papers/TOJ-22-0073_152Mendoza.pdf\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.external.pypdf_loader\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:33.827021\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.066870\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.216488\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `49b3ca10-a420-5f3d-b7c1-88e5074b4697`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.416238\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mOntology file 'examples/python/ontology_input_example/enriched_medical_ontology_with_classes.owl' not found. No owl ontology will be attached to the graph.\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.446910\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `0777e6d7-7d59-5c50-9970-c0f3cc61ad17`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.595357\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.745824\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:34.922225\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task started: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:37:35.152064\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:37:35 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:37:35 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:37:35 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.979669\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'article' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.980959\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee consumption and all-cause, cardiovascular, and cancer mortality in an adult mediterranean population' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.981373\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'person' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.981688\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'laura torres-collado' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.982010\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'laura maría compañ-gabucio' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.982248\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'sandra gonzález-palacios' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.982524\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'leyre notario-barandiaran' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.982826\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'alejandro oncina-cánovas' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.983093\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'jesús vioque' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.983411\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'manuela garcía-de la hera' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.983715\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'journal' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.983916\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'nutrients' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.984159\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'identifier' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.984540\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '10.3390/nu13041241' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.984791\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.985029\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia nutrition survey 1994' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.985265\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'location' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.985494\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia spain' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.985743\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'metric' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.985984\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '1567 participants' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.986218\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'date' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.986402\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '1994' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.986678\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '2012' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.986931\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '18 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.987142\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '317 deaths' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.987368\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '115 cvd deaths' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.987579\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '82 cancer deaths' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.987781\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'concept' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.988025\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.988255\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'caffeinated coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.988463\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'decaffeinated coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.988680\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'non-drinker' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.988900\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '≤1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.989091\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '>1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.989241\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause ≤1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.989565\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.989790\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr cancer >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.990193\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr caffeinated all-cause 12 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.990554\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr caffeinated all-cause 18 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.990913\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia nutrition survey' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.991159\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'spain' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.991326\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cohort' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.991509\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cohort of 1567 participants' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.991682\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '6-year follow-up' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.991843\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '12-year follow-up' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.992094\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '18-year follow-up' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.992434\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'exposure' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.992626\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'total coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.992814\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'category' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.993560\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'non-drinkers' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.994015\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'up to 1 cup per day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.994265\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'more than 1 cup per day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.994535\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'outcome' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.994695\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.995174\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.995608\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cancer mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.996422\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'statistic' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.996852\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 18yr <=1 cup' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.997429\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 18yr >1 cup' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.998117\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr cancer 18yr >1 cup' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.998567\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr caffeinated all-cause 18yr' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.998936\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'decaffeinated no significant association' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.999428\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee consumption (1-6.5 cups/day)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:24.999813\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.000380\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.000897\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencian nutrition survey (vns)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.001368\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'nutrients 2021 publication' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.002073\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee associated with lower all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.003004\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee associated with lower cancer mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.003858\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'limitation' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.004856\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'small sample size' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.005713\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'no coffee preparation information' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.006065\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'volunteer response bias' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.006541\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'preexisting chronic illness confounding' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.006868\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'strength' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.007153\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'well-defined population' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.007442\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'trained fieldworkers' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.007667\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'standardized protocols and validated questionnaires' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.007921\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'prospective data collection' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.008426\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'organization' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.008640\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'generalitat valenciana' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.009416\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'fondo investigacion sanitaria (fis)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.009743\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'instituto de salud carlos iii' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.010051\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'feder funds' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.010553\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hospital of san juan ethical committee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.010989\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'miguel hernandez university ethical committee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.011698\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'informed consent' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.012903\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'data availability on request' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.014060\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'j.v.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.015064\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'm.g.-d.l.h.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.015627\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.t.-c.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.016207\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.m.c.-g.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.016647\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 's.g.-p.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.017039\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.n.-b.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.017346\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'a.o.-c.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:25.017938\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'publication date 2021' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:29.091175\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:39:29 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:39:29 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:39:29 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:42.154602\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:46.447966\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:46.593731\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:46.741331\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:46.892908\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task completed: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.041862\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.189093\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.359462\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `0777e6d7-7d59-5c50-9970-c0f3cc61ad17`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.523959\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `0777e6d7-7d59-5c50-9970-c0f3cc61ad17`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.675233\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:47.826574\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:48.003405\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task started: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:39:48.221678\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:39:48 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:39:48 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.905392\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'article' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.907628\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'impact of coffee consumption on cardiovascular health (ochsner journal 2023)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.908013\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'person' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.908484\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'michael f. mendoza' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.908766\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ralf martz sulague' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.909072\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'therese posas-mendoza' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.909368\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'carl j. lavie' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.909752\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'concept' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.910138\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.910410\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'compound' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.911344\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'caffeine' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.913767\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cafestol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.915021\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'kahweol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.916064\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'chlorogenic acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.916634\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'phenolic acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.917565\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'boiled or unfiltered coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.918619\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'filtered coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.919556\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'decaffeinated coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.920353\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.925672\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'disease' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.928353\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hypertension' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.929122\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coronary heart disease' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.929696\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'myocardial infarction' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.930682\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'heart failure' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.935900\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'atrial fibrillation' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.938047\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.938643\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.939222\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'jee 1999' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.939575\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'jenner 1988' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.939862\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'miranda 2021' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.940109\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'harvest 2009' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.940295\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'post 1997' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.940473\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'uto-kondo 2010' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.940653\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'sarriá 2018' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.940898\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cornelis 2006' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.941088\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'grioni 2015' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.941318\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'sofi 2007' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.941590\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'zhou and hyppönen 2019' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.941778\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mostofsky 2012' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.941955\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'stevens 2021' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.942127\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'bodar 2019' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.942290\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cheng 2014' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.942570\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'brown 2016' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.943233\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'beverage' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.943502\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.943762\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'high (heavy) coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.944006\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'polyphenol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.944230\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'trigonelline' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.944396\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'quinide' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.945138\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'magnesium' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.945698\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'boiled coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.946300\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'process' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.947076\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'antioxidant effects' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.947388\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'anti-inflammatory processes' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.947641\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'bile acid synthesis inhibition' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.948126\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hdl-mediated cholesterol efflux' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.949246\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.951136\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.951625\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'gene' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.951847\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2 genotype' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.952130\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'smoking status' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.952385\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ali-hassan-sayegh et al 2014' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.952620\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ding et al 2015' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.952879\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'lopez-garcia et al 2008' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.953072\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'kim et al 2019' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.953262\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'framingham heart study (fhs)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.953465\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'boiled coffee effect on cholesterol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:00.953778\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'filtered coffee antiatherogenic effect' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:04.775775\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:41:04 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:41:04 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:16.909016\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:23.405479\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:23.551481\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:23.704043\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:23.866120\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task completed: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:24.016613\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:24.178170\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:24.349765\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `0777e6d7-7d59-5c50-9970-c0f3cc61ad17`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:24.689399\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 170 nodes, 464 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:25.111042\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.03s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:41:25 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:34.706451\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 170 nodes, 464 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:35.190814\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:41:35 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:46.935908\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 170 nodes, 464 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:41:47.406589\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:41:47 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:04.430219\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 170 nodes, 464 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:04.929193\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:42:05 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Q: What are common risk factors for Type 2 Diabetes?\n",
"A: ['Preparing brief answer using the provided context.']\n",
"\n",
"Q: What preventive measures reduce the risk of Hypertension?\n",
"A: ['Preparing a brief evidence-based answer from the provided context about measures that reduce risk of hypertension.']\n",
"\n",
"Q: What symptoms indicate possible Cardiovascular Disease?\n",
"A: ['Acknowledged.']\n",
"\n",
"Q: What diseases are associated with Obesity?\n",
"A: ['Acknowledged.']\n",
"\n"
]
}
],
"source": [
"# Test questions\n",
"questions = [\n",
" \"What are common risk factors for Type 2 Diabetes?\",\n",
" \"What preventive measures reduce the risk of Hypertension?\",\n",
" \"What symptoms indicate possible Cardiovascular Disease?\",\n",
" \"What diseases are associated with Obesity?\"\n",
"]\n",
"\n",
"# Path to medical ontology\n",
"ontology_path = \"examples/python/ontology_input_example/enriched_medical_ontology_with_classes.owl\" # Update with your ontology path\n",
"\n",
"# Run with ontology\n",
"print(\"\\n--- Results WITH ontology ---\\n\")\n",
"await run_pipeline(ontology_path=ontology_path)\n",
"answers_with = await query_pipeline(questions)\n",
"for q, a in zip(questions, answers_with):\n",
" print(f\"Q: {q}\\nA: {a}\\n\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3aa18f4cdd5ceff6",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T14:32:24.891560Z",
"start_time": "2025-04-09T14:30:47.863808Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:42:17.046125\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDeleted Kuzu database files at /Users/daulet/Desktop/dev/cognee-claude/cognee/.cognee_system/databases/cognee_graph_kuzu\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:17.139414\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mDatabase deleted successfully.\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"--- Results WITHOUT ontology ---\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:42:17.270853\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `ab71824c-9eb0-5863-a3a2-0bfd328f0f8f`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:17.424882\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"User cbbb7ebc-556b-428f-9cf9-55bc1a277254 has registered.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:42:17.573292\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:17.752197\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mReading PDF: /Users/daulet/Desktop/dev/cognee/examples/data/scientific_papers/nutrients-13-01241.pdf\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.external.pypdf_loader\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:17.879186\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.016115\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.164058\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `ab71824c-9eb0-5863-a3a2-0bfd328f0f8f`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.334120\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `ab71824c-9eb0-5863-a3a2-0bfd328f0f8f`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.486127\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.628970\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.801360\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mReading PDF: /Users/daulet/Desktop/dev/cognee/examples/data/scientific_papers/TOJ-22-0073_152Mendoza.pdf\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.infrastructure.loaders.external.pypdf_loader\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:18.908548\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `ingest_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.047269\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `resolve_data_directories`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.190568\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `ab71824c-9eb0-5863-a3a2-0bfd328f0f8f`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.357382\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mOntology file 'None' not found. No owl ontology will be attached to the graph.\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.386538\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `b255fc1d-2d5b-51c5-b36a-28262bb970a5`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.538272\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:19.950142\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:20.106539\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task started: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:42:20.292885\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:42:20 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:42:20 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:42:20 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.119474\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'article' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.122494\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee consumption and all-cause, cardiovascular, and cancer mortality in an adult mediterranean population' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.122927\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'person' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.123301\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'laura torres-collado' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.123589\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'laura maría compañ-gabucio' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.123892\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'sandra gonzález-palacios' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.124198\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'leyre notario-barandiaran' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.124537\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'alejandro oncina-cánovas' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.124855\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'jesús vioque' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.125120\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'manuela garcía-de la hera' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.125372\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'organization' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.125654\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'instituto de investigación sanitaria y biomédica de alicante (isabial-umh)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.125943\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'universidad miguel hernández (umh)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.126125\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.126331\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia nutrition survey' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.126589\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'date' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.127058\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '1994' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.127296\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '18 years follow-up' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.127528\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'method' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.127803\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'food frequency questionnaire' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.128045\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'food' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.128287\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'caffeinated coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.128567\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'decaffeinated coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.128799\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'metric' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.129018\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'total coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.129220\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study population 1567 adults' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.129460\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'outcome' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.129698\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.129926\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.130167\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cancer mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.130406\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'statistic' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.130630\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hazard ratio all-cause <=1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.130883\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hazard ratio all-cause >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.131044\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hazard ratio cancer >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.131246\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hazard ratio caffeinated 12 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.131435\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hazard ratio caffeinated 18 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.131631\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'nutrients' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.132150\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'location' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.132310\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia, spain' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.132723\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencia nutrition survey' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.132953\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'exposure' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.133131\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.133377\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.133575\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.133795\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cancer mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.133982\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'follow-up 6 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.134154\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'follow-up 12 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.134349\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'follow-up 18 years' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.134519\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 6y >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.134774\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 12y >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.135108\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 18y ≤1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.135384\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr all-cause 18y >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.135669\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr cancer 18y >1 cup/day' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.135931\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hr caffeinated all-cause 18y' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.136107\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'figure' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.136294\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'figure 1' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.138388\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'table' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.138958\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'table 2' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.139300\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'table 3' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.140243\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'concept' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.141152\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'unfiltered coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.141440\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee consumption (16.5 cups/day)' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.141668\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.141858\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.142035\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'vns study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.142260\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'population' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.142538\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'valencian adult population' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.142733\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'baseline self-report' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.142918\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study_feature' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.143169\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'long follow-up period' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.144208\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'limitation' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.146800\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'small sample size' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.148681\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'pre-existing chronic disease' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.149240\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'analysis' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.151022\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'excluding deaths in the first and second year' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.152981\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee preparation method not collected' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.154280\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'spain' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.157482\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mediterranean lifestyle' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.157941\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'funding' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.163422\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'funding sources' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.165738\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ethics' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.169106\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ethical approval' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.170720\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'policy' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.171293\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'data availability' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.171614\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'finding' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.171849\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'associations unchanged after excluding early deaths' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.172191\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'j.v.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.172428\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'm.g.-d.l.h.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.172619\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.t.-c.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.172918\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.m.c.-g.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.173120\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 's.g.-p.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.173272\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'l.n.-b.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:29.173510\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'a.o.-c.' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:34.235408\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:43:34 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:43:34 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:43:34 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:49.801524\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:54.774594\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:54.952836\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.105797\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.244447\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task completed: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.395452\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.539861\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.690061\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `b255fc1d-2d5b-51c5-b36a-28262bb970a5`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:55.873677\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run started: `b255fc1d-2d5b-51c5-b36a-28262bb970a5`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:56.025990\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:56.169166\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:56.341935\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task started: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:43:56.531753\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:43:56 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:43:56 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.808776\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'substance' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.811704\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.812785\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'caffeine' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.813409\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'boiled coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.813786\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'filtered coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.814115\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cafestol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.814433\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'kahweol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.814751\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'phenolic acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.815097\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'protein' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.815341\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'abcg1' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.815632\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'sr-bi' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.816005\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'biomarker' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.816367\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cholesterol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.816661\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hdl' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.816965\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'disease' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.817263\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hypertension' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.817539\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'measurement' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.817831\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'blood pressure' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.818122\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'heart failure' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.818358\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'atrial fibrillation' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.818606\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'coronary heart disease' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.818874\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'myocardial infarction' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.819194\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'outcome' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.819569\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.819781\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'enzyme' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.820018\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.820285\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'variant' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.820528\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2*1f' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.820791\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2*1a' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.821038\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'behavior' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.821304\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'smoking' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.821550\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'state' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.821776\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'pregnancy' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.821971\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'guideline' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.822241\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for '300 mg caffeine per day guideline' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.822503\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'green coffee' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.822746\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'study' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.823011\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mendoza et al 2023' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.823231\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cornelis et al 2006' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.823520\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mostofsky et al 2012' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.823759\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'bodar et al 2019' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.823970\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'stevens et al 2021' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.824435\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'compound' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.824615\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'polyphenol' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.824848\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'trigonelline' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.825106\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'chlorogenic acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.825312\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'quinide' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.825599\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ferulic acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.825856\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'p-coumaric acid' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.826065\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'mineral' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.826268\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'magnesium' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.826516\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'n-acetylcysteine' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.826754\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'polyunsaturated fatty acids' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.826962\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'biological_process' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.831202\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'anti-inflammatory processes' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.831539\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'all-cause mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.831809\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular disease mortality' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.832041\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'preparation' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.832294\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'hdl-mediated cholesterol efflux' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.832576\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'gene' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.832870\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cyp1a2 genotype' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.833074\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'smoking status' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.833334\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'consumptionlevel' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.833545\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'moderate coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.833938\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'high coffee consumption' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.834315\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'meta_analysis' in category 'classes'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.834516\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ali-hassan-sayegh et al 2014' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.834735\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'ding et al 2015' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.834977\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'lopez-garcia et al 2008' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.835179\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'de koning gans et al 2010' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.835438\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'andersen et al 2006' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.836010\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'kleemola et al 2000' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.836242\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'kim et al 2019' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.836647\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'framingham heart study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.836933\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardiovascular health study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.837359\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'atherosclerosis risk in communities study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.837810\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'physicians health study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:26.838177\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mNo close match found for 'cardia study' in category 'individuals'\u001b[0m [\u001b[0m\u001b[1m\u001b[34mOntologyAdapter\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:31.122928\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\u001b[92m14:45:31 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\u001b[92m14:45:31 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:43.793543\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task started: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:48.632018\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `add_data_points`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:48.784320\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `summarize_text`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:48.942072\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `extract_graph_from_data`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:49.096404\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mAsync Generator task completed: `extract_chunks_from_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:49.251314\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `check_permissions_on_dataset`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:49.411272\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mCoroutine task completed: `classify_documents`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_base\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:49.563539\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mPipeline run completed: `b255fc1d-2d5b-51c5-b36a-28262bb970a5`\u001b[0m [\u001b[0m\u001b[1m\u001b[34mrun_tasks_with_telemetry()\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:50.149392\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 178 nodes, 445 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:50.682374\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:45:50 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:58.803572\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 178 nodes, 445 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:45:59.339015\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:45:59 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:46:11.327531\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 178 nodes, 445 edges in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:46:11.815541\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:46:11 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:46:21.754939\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph projection completed: 178 nodes, 445 edges in 0.01s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mCogneeGraph\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:46:22.332430\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mVector collection retrieval completed: Retrieved distances from 6 collections in 0.02s\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\u001b[92m14:46:22 - LiteLLM:INFO\u001b[0m: utils.py:3341 - \n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\n",
"\n",
"\u001b[1m\n",
"LiteLLM completion() model= gpt-5-mini; provider = openai\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Q: What are common risk factors for Type 2 Diabetes?\n",
"A: ['Using provided context to prepare a brief answer about common Type 2 diabetes risk factors.']\n",
"\n",
"Q: What preventive measures reduce the risk of Hypertension?\n",
"A: ['Preparing a brief, context-based answer on preventive measures that reduce risk of hypertension.']\n",
"\n",
"Q: What symptoms indicate possible Cardiovascular Disease?\n",
"A: ['Common symptoms that can indicate possible cardiovascular disease:\\n- Chest pain, pressure, squeezing or discomfort (angina)\\n- Shortness of breath or difficulty breathing\\n- Palpitations, an irregular or fast heartbeat (possible atrial fibrillation)\\n- Lightheadedness, dizziness, or fainting (syncope)\\n- Unexplained fatigue or reduced exercise tolerance\\n- Swelling in the legs, ankles or abdomen (fluid retention/heart failure)\\n- Sudden weakness, numbness, slurred speech, or vision changes (possible stroke)\\n\\nIf someone has chest pain, sudden severe shortness of breath, fainting, or stroke-like symptoms, seek emergency care immediately.']\n",
"\n",
"Q: What diseases are associated with Obesity?\n",
"A: ['Type 2 diabetes; hypertension; coronary heart disease and other cardiovascular diseases (atherosclerosis, heart failure, atrial fibrillation); certain cancers; and increased allcause mortality.']\n",
"\n"
]
}
],
"source": [
"# Run without ontology\n",
"print(\"\\n--- Results WITHOUT ontology ---\\n\")\n",
"await run_pipeline()\n",
"answers_without = await query_pipeline(questions)\n",
"for q, a in zip(questions, answers_without):\n",
" print(f\"Q: {q}\\nA: {a}\\n\")"
]
},
{
"cell_type": "markdown",
"id": "c60533d2423acdb0",
"metadata": {},
"source": [
"## Visualizing the Knowledge Graph\n",
"\n",
"Let's visualize how our ontology connects different medical concepts:"
]
},
{
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"end_time": "2025-04-09T15:25:33.512697Z",
"start_time": "2025-04-09T15:25:33.471854Z"
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{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"\u001b[2m2025-08-27T13:46:35.623071\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mGraph visualization saved as /Users/daulet/graph_visualization.html\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n",
"\n",
"\u001b[2m2025-08-27T13:46:35.626149\u001b[0m [\u001b[32m\u001b[1minfo \u001b[0m] \u001b[1mThe HTML file has been stored on your home directory! Navigate there with cd ~\u001b[0m [\u001b[0m\u001b[1m\u001b[34mcognee.shared.logging_utils\u001b[0m]\u001b[0m\n"
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{
"data": {
"text/plain": [
"True"
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},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import webbrowser\n",
"import os\n",
"from cognee.api.v1.visualize.visualize import visualize_graph\n",
"html = await visualize_graph()\n",
"home_dir = os.path.expanduser(\"~\")\n",
"html_file = os.path.join(home_dir, \"graph_visualization.html\")\n",
"display(html_file)\n",
"webbrowser.open(f\"file://{html_file}\")"
]
},
{
"cell_type": "markdown",
"id": "ff39326921b75273",
"metadata": {},
"source": [
"## Understanding the Results\n",
"\n",
"The demonstration above shows how ontologies enhance our analysis by:\n",
"\n",
"1. **Making Connections**: \n",
" - Linking related medical concepts even when not explicitly stated\n",
" - Identifying relationships between symptoms, diseases, and risk factors\n",
"\n",
"2. **Standardizing Terms**: \n",
" - Unifying different ways of referring to the same medical condition\n",
" - Ensuring consistent terminology across documents\n",
"\n",
"3. **Enabling Inference**: \n",
" - Drawing conclusions based on ontological relationships\n",
" - Discovering implicit connections in the data\n",
"\n",
"## Next Steps\n",
"\n",
"To learn more about Cognee and ontologies:\n",
"1. Check out the [Cognee documentation](https://docs.cognee.ai/)\n",
"2. Explore more examples in the `examples` directory\n",
"3. Try creating your own domain-specific ontology\n",
"\n",
"Remember to:\n",
"- Place your scientific papers in the appropriate directory\n",
"- Update the ontology path to point to your .owl file\n",
"- Replace the API key with your own OpenAI key"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8d2a0fe555a7bc0f",
"metadata": {},
"outputs": [
{
"ename": "",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
"\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
"\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
"\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
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}
],
"source": [
"import os\n",
"os._exit(0)"
]
}
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"display_name": ".venv",
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