{ "cells": [ { "metadata": {}, "cell_type": "markdown", "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" ], "id": "25cf0a40e669a70" }, { "metadata": {}, "cell_type": "markdown", "source": [ "## Setup\n", "\n", "First, let's install the required packages and set up our environment:" ], "id": "441248da37f2b901" }, { "metadata": { "ExecuteTime": { "end_time": "2025-03-26T16:17:55.937140Z", "start_time": "2025-03-26T16:17:55.908542Z" } }, "cell_type": "code", "source": [ "# Install required package\n", "# !pip install cognee" ], "id": "8cf7ba29f9a150af", "outputs": [], "execution_count": 17 }, { "metadata": { "ExecuteTime": { "end_time": "2025-03-26T16:18:09.382400Z", "start_time": "2025-03-26T16:18:09.342349Z" } }, "cell_type": "code", "source": [ "# Import required libraries\n", "import cognee\n", "import asyncio\n", "from cognee.shared.logging_utils import get_logger\n", "import os\n", "import textwrap\n", "from cognee.api.v1.search import SearchType\n", "from cognee.api.v1.visualize.visualize import visualize_graph\n", "\n", "logger = get_logger()\n", "\n", "# Set up OpenAI API key (required for Cognee's LLM functionality)\n", "os.environ[\"LLM_API_KEY\"] = \"your-api-key-here\" # Replace with your API key" ], "id": "d825d126b3a0ec26", "outputs": [], "execution_count": 18 }, { "metadata": {}, "cell_type": "markdown", "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" ], "id": "6af350837e86b7a1" }, { "metadata": { "ExecuteTime": { "end_time": "2025-04-09T17:12:54.006718Z", "start_time": "2025-04-09T17:12:53.992906Z" } }, "cell_type": "code", "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" ], "id": "4d0e4a58e4207a7d", "outputs": [], "execution_count": 26 }, { "metadata": {}, "cell_type": "markdown", "source": [ "## Running the Demo\n", "\n", "Let's test our system with some medical questions, comparing results with and without ontological knowledge:" ], "id": "c87c21a75d6f4d79" }, { "metadata": { "ExecuteTime": { "end_time": "2025-04-09T17:14:31.818452Z", "start_time": "2025-04-09T17:12:55.491598Z" } }, "cell_type": "code", "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\")" ], "id": "1363772d2b48f5c0", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "--- Results WITH ontology ---\n", "\n", "\n", "\u001B[2m2025-04-09T17:12:55.499538Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mGraph deleted successfully. \u001B[0m [\u001B[0m\u001B[1m\u001B[34mcognee.shared.logging_utils\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:55.588613Z\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[0mUser 312efe9d-380c-4f8d-9848-f628fe3dc177 has registered.\n", "\n", "\n", "\u001B[2m2025-04-09T17:12:55.747683Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run started: `4b84e400-23fc-5976-bbb4-f8ee303eed81`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:55.749122Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `resolve_data_directories`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:55.750745Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `ingest_data`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.069185Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `ingest_data`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.069591Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `resolve_data_directories`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.070114Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run completed: `4b84e400-23fc-5976-bbb4-f8ee303eed81`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\n", "\u001B[2m2025-04-09T17:12:56.081871Z\u001B[0m [\u001B[33m\u001B[1mwarning \u001B[0m] \u001B[1mOntology file 'examples/python/ontology_input_example/enriched_medical_ontology_with_classes.owl' not found. Using fallback ontology at http://example.org/empty_ontology\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.083270Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mLookup built: 0 classes, 0 individuals\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.099230Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run started: `af81ab41-8243-522f-a10a-b7b5febcc577`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.100778Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `classify_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.102874Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `check_permissions_on_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:12:56.105891Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/vasilije/cognee/.venv/lib/python3.11/site-packages/dlt/destinations/impl/sqlalchemy/merge_job.py:194: SAWarning: Table 'file_metadata' already exists within the given MetaData - not copying.\n", " staging_table_obj = table_obj.to_metadata(\n", "/Users/vasilije/cognee/.venv/lib/python3.11/site-packages/dlt/destinations/impl/sqlalchemy/merge_job.py:229: SAWarning: implicitly coercing SELECT object to scalar subquery; please use the .scalar_subquery() method to produce a scalar subquery.\n", " order_by=order_dir_func(order_by_col),\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[2m2025-04-09T17:12:56.490952Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:12:56 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.028895Z\u001B[0m [\u001B[33m\u001B[1mwarning \u001B[0m] \u001B[1mFile /Users/vasilije/cognee/cognee/.cognee_system/databases/cognee_graph.pkl not found. Initializing an empty graph.\u001B[0m [\u001B[0m\u001B[1m\u001B[34mcognee.shared.logging_utils\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.031340Z\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", "\u001B[2m2025-04-09T17:13:45.031582Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee consumption study' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.031815Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'nutrient' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.032000Z\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", "\u001B[2m2025-04-09T17:13:45.032523Z\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", "\u001B[2m2025-04-09T17:13:45.032768Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health outcome' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.033005Z\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", "\u001B[2m2025-04-09T17:13:45.033326Z\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", "\u001B[2m2025-04-09T17:13:45.033618Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'participant population' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.033907Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'dietary pattern' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.034121Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mediterranean diet' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.034391Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'eureye spain and valencia nutrition study' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.034592Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'statistical measurement' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.034943Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'p-value' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.035127Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'risk of death' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.035397Z\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", "\u001B[2m2025-04-09T17:13:45.035564Z\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", "\u001B[2m2025-04-09T17:13:45.035764Z\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", "\u001B[2m2025-04-09T17:13:45.035957Z\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", "\u001B[2m2025-04-09T17:13:45.036177Z\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", "\u001B[2m2025-04-09T17:13:45.036551Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'beverage type' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.036791Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'demographic characteristic' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.036971Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'sex distribution' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.037179Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'age distribution' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.037412Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'education level' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.037593Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health indicator' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.037748Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'body mass index' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.037952Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'waist circumference' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.038237Z\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", "\u001B[2m2025-04-09T17:13:45.038622Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health condition' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.038857Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'diabetes status' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.039193Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cholesterol status' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.039524Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'hypertension status' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.039801Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'physical activity' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.040067Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'tv watching' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.040355Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'sleeping time' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.040619Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'dietary index' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.040847Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'relative mediterranean diet index' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.041182Z\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", "\u001B[2m2025-04-09T17:13:45.041404Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'group' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.041719Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mediterranean population' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.041914Z\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", "\u001B[2m2025-04-09T17:13:45.042158Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'research' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.042377Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'study 2021' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.042579Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'country' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.043107Z\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", "\u001B[2m2025-04-09T17:13:45.043321Z\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", "\u001B[2m2025-04-09T17:13:45.043627Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'torres-collado, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.043899Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'garcia-de-la-hera, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.044128Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'navarrete-muñoz, e.m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.044345Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'notario-barandiaran, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.044588Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gonzalez-palacios, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.044959Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'zurriaga, o.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.045232Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'melchor, i.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.045447Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'vioque, j.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.045630Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'navarro, a.m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.045956Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'martinez-gonzalez, m. á.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.046206Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gea, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.046422Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'grosso, g.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.046629Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'martin-moreno, j.m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.046939Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'lopez-garcia, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.047166Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'martin-calvo, n.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.047426Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'toledo, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.047719Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'ruggiero, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.048060Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'di castelnuovo, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.048339Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'costanzo, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.048603Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'persichillo, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.048831Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'de curtis, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.049031Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cerletti, c.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.049243Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'donati, m.b.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.049458Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'de gaetano, g.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.049693Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'iacoviello, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.049907Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'bonaccio, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.050227Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'moli-sani study' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.050482Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'quiles, j.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.050703Z\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", "\u001B[2m2025-04-09T17:13:45.050875Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'u.s. department of agriculture' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.051151Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'database' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.051437Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'usda national nutrient database' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.051639Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'palma, i.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.051816Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cantós, d.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.052024Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'lean, m.e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.052242Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'harlow, s.d.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.052466Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'malerba, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.052723Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'crippa, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.052949Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'je, y.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.053201Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'park, s.-y.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.053447Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gunter, m.j.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.053667Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'sado, j.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.053863Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'dinu, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.054068Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gökcen, b.b.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.054375Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'yu, x.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.054586Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gonzalez de mejia, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.054764Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'yamagata, k.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.054991Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'machado-fragua, m.d.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.055251Z\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", "\u001B[2m2025-04-09T17:13:45.055480Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '2018' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.056014Z\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", "\u001B[2m2025-04-09T17:13:45.056232Z\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", "\u001B[2m2025-04-09T17:13:45.056451Z\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", "\u001B[2m2025-04-09T17:13:45.056709Z\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", "\u001B[2m2025-04-09T17:13:45.057211Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'publication' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.057503Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'ochsner journal' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.057723Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cardiovascular health' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.057989Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'impact of coffee consumption on cardiovascular health' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.058182Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'condition' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.058357Z\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", "\u001B[2m2025-04-09T17:13:45.058542Z\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", "\u001B[2m2025-04-09T17:13:45.058710Z\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", "\u001B[2m2025-04-09T17:13:45.058870Z\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", "\u001B[2m2025-04-09T17:13:45.059039Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '2000-2021' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.059210Z\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", "\u001B[2m2025-04-09T17:13:45.059397Z\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", "\u001B[2m2025-04-09T17:13:45.059735Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mendoza, mf' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.060066Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coronary artery risk development in young adults study' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:13:45.060328Z\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", "\u001B[2m2025-04-09T17:13:52.506030Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `summarize_text`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:13:52 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m\n", "\u001B[2m2025-04-09T17:13:58.267490Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `add_data_points`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.439855Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `add_data_points`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.440337Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `summarize_text`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.440524Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.440690Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.440886Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `check_permissions_on_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.441125Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `classify_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T17:14:07.441383Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run completed: `af81ab41-8243-522f-a10a-b7b5febcc577`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:14:09 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:14:23 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:14:27 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m19:14:30 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0mQ: What are common risk factors for Type 2 Diabetes?\n", "A: ['Common risk factors for Type 2 Diabetes include:\\n1. **Obesity** - particularly a high body mass index (BMI) (≥30 kg/m2).\\n2. **Waist circumference** - increased risk is associated with larger waist sizes.\\n3. **Sedentary lifestyle** - low levels of physical activity are linked to higher risk.\\n4. **Age** - the risk increases with age, especially for those over 45 years.\\n5. **Diet** - poor dietary choices, including low adherence to a Mediterranean diet, may contribute.\\n6. **Smoking** - current smoking status is a risk factor.\\n7. **Hypertension** - having high blood pressure increases risk.\\n8. **Cholesterol levels** - high cholesterol levels may also be a factor.']\n", "\n", "Q: What preventive measures reduce the risk of Hypertension?\n", "A: ['Preventive measures to reduce the risk of hypertension include moderate coffee consumption, which has been associated with a decreased risk of developing hypertension, particularly in non-smokers. Other potential mechanisms of benefit from coffee include inhibition of sodium and water reabsorption, as well as anti-inflammatory effects.']\n", "\n", "Q: What symptoms indicate possible Cardiovascular Disease?\n", "A: ['Possible symptoms indicating cardiovascular disease include: hypertension, heart failure, atrial fibrillation, elevated cholesterol levels, and increased risk of myocardial infarction. Regular coffee consumption is associated with decreased risks of some of these conditions, whereas heavy coffee consumption may have inconsistent effects.']\n", "\n", "Q: What diseases are associated with Obesity?\n", "A: ['Obesity is associated with the following health conditions:\\n1. Cardiovascular disease mortality (as a health outcome).\\n2. Diabetes status (as a health condition).\\n3. Cholesterol status (as a health condition).']\n", "\n" ] } ], "execution_count": 27 }, { "metadata": {}, "cell_type": "code", "outputs": [], "execution_count": null, "source": "", "id": "89e2e53dcecb78eb" }, { "metadata": { "ExecuteTime": { "end_time": "2025-04-09T14:32:24.891560Z", "start_time": "2025-04-09T14:30:47.863808Z" } }, "cell_type": "code", "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\")" ], "id": "3aa18f4cdd5ceff6", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "--- Results WITHOUT ontology ---\n", "\n", "\n", "\u001B[2m2025-04-09T14:30:47.865578Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mGraph deleted successfully. \u001B[0m [\u001B[0m\u001B[1m\u001B[34mcognee.shared.logging_utils\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:47.879242Z\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[0mUser 5fcea8fd-95ce-4a3b-861e-d8f8a5d01fe5 has registered.\n", "\n", "\n", "\u001B[2m2025-04-09T14:30:47.952091Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run started: `4b84e400-23fc-5976-bbb4-f8ee303eed81`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:47.952386Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `resolve_data_directories`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:47.952810Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `ingest_data`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.127543Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `ingest_data`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.127926Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task completed: `resolve_data_directories`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.128135Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run completed: `4b84e400-23fc-5976-bbb4-f8ee303eed81`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\n", "\u001B[2m2025-04-09T14:30:48.135862Z\u001B[0m [\u001B[33m\u001B[1mwarning \u001B[0m] \u001B[1mOntology file 'None' not found. Using fallback ontology at http://example.org/empty_ontology\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.136338Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mLookup built: 0 classes, 0 individuals\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.145025Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mPipeline run started: `af81ab41-8243-522f-a10a-b7b5febcc577`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.145316Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `classify_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.145568Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `check_permissions_on_documents`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:30:48.148188Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/vasilije/cognee/.venv/lib/python3.11/site-packages/dlt/destinations/impl/sqlalchemy/merge_job.py:194: SAWarning: Table 'file_metadata' already exists within the given MetaData - not copying.\n", " staging_table_obj = table_obj.to_metadata(\n", "/Users/vasilije/cognee/.venv/lib/python3.11/site-packages/dlt/destinations/impl/sqlalchemy/merge_job.py:229: SAWarning: implicitly coercing SELECT object to scalar subquery; please use the .scalar_subquery() method to produce a scalar subquery.\n", " order_by=order_dir_func(order_by_col),\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[2m2025-04-09T14:30:48.491623Z\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(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:30:48 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.725114Z\u001B[0m [\u001B[33m\u001B[1mwarning \u001B[0m] \u001B[1mFile /Users/vasilije/cognee/cognee/.cognee_system/databases/cognee_graph.pkl not found. Initializing an empty graph.\u001B[0m [\u001B[0m\u001B[1m\u001B[34mcognee.shared.logging_utils\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.728424Z\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", "\u001B[2m2025-04-09T14:31:53.728765Z\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", "\u001B[2m2025-04-09T14:31:53.729061Z\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", "\u001B[2m2025-04-09T14:31:53.729298Z\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", "\u001B[2m2025-04-09T14:31:53.729489Z\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", "\u001B[2m2025-04-09T14:31:53.729721Z\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", "\u001B[2m2025-04-09T14:31:53.729906Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'ochsner clinic foundation' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.730134Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'georgetown university' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.730308Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'publication' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.730488Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'ochsner journal' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.730684Z\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", "\u001B[2m2025-04-09T14:31:53.730862Z\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", "\u001B[2m2025-04-09T14:31:53.731104Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cardiovascular health' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.731289Z\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", "\u001B[2m2025-04-09T14:31:53.731461Z\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", "\u001B[2m2025-04-09T14:31:53.731690Z\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", "\u001B[2m2025-04-09T14:31:53.731955Z\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", "\u001B[2m2025-04-09T14:31:53.732126Z\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", "\u001B[2m2025-04-09T14:31:53.732315Z\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", "\u001B[2m2025-04-09T14:31:53.732488Z\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", "\u001B[2m2025-04-09T14:31:53.732691Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'diterpenes' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.732873Z\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", "\u001B[2m2025-04-09T14:31:53.733046Z\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", "\u001B[2m2025-04-09T14:31:53.733274Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee preparation methods' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.733593Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mendoza, mf' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.733935Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'diabetes mellitus' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.734489Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'infarction' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.734817Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'left ventricular function' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.735100Z\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", "\u001B[2m2025-04-09T14:31:53.735288Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'oxidative stress' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.735482Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'research methodology' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.735649Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'meta-analysis' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.735816Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'antioxidants' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.736048Z\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", "\u001B[2m2025-04-09T14:31:53.736250Z\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", "\u001B[2m2025-04-09T14:31:53.736442Z\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", "\u001B[2m2025-04-09T14:31:53.736626Z\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", "\u001B[2m2025-04-09T14:31:53.736796Z\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", "\u001B[2m2025-04-09T14:31:53.736959Z\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", "\u001B[2m2025-04-09T14:31:53.737123Z\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", "\u001B[2m2025-04-09T14:31:53.737288Z\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", "\u001B[2m2025-04-09T14:31:53.737436Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'nutrients 2021' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.737591Z\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", "\u001B[2m2025-04-09T14:31:53.737782Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'valencia nutrition study' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.738030Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'eureye-spain' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.738267Z\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", "\u001B[2m2025-04-09T14:31:53.738422Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'demographic' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.738578Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'participants aged 20 years and above' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.738743Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health metric' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.739188Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'age' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.739521Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'education level' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.739834Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'body mass index (bmi)' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.740034Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'waist circumference' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.740213Z\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", "\u001B[2m2025-04-09T14:31:53.740388Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'diabetes' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.740719Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'physical activity' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.740905Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'tv watching' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.741075Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'sleeping time' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.741375Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'rmed index' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.741550Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '6 years follow-up mortality' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.741725Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '12 years follow-up mortality' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.741889Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '18 years follow-up mortality' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.742134Z\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", "\u001B[2m2025-04-09T14:31:53.742306Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mediterranean population' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.742479Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health behavior' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.742802Z\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", "\u001B[2m2025-04-09T14:31:53.743001Z\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", "\u001B[2m2025-04-09T14:31:53.743187Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'health outcome' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.743374Z\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", "\u001B[2m2025-04-09T14:31:53.743543Z\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", "\u001B[2m2025-04-09T14:31:53.743722Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cvd mortality' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.743892Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'country' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.744058Z\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", "\u001B[2m2025-04-09T14:31:53.744231Z\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", "\u001B[2m2025-04-09T14:31:53.744483Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'scientific concept' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.744647Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'biological mechanisms' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.744831Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'research participants' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.745001Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'chemical' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.745162Z\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", "\u001B[2m2025-04-09T14:31:53.745435Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'torres-collado, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.745639Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'garcia-de-la-hera, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.745808Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'navarrete-muñoz, e.m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.746008Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'notario-barandiaran, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.746185Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gonzalez-palacios, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.746657Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'zurriaga, o.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.746868Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'melchor, i.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.747422Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'vioque, j.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.747692Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'navarro, a.m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.747904Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'martinez-gonzalez, m.á.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748081Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gea, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748254Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'grosso, g.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748421Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'ruggiero, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748580Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'di castelnuovo, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748758Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'costanzo, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.748926Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'persichillo, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.749109Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'de curtis, a.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.749301Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'cerletti, c.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.749494Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'donati, m.b.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.749667Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'de gaetano, g.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.749845Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'iacoviello, l.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.750035Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'bonaccio, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.750210Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'harlow, s.d.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.750388Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'linet, m.s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.750567Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'malerba, s.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.750830Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'dinu, m.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.751026Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'yu, x.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.751207Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gonzalez de mejia, e.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.751368Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'yamagata, k.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.751619Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'gökcen, b.b.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.751870Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'machado-fragua, m.d.' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.752101Z\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", "\u001B[2m2025-04-09T14:31:53.752294Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '2018-01-01' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.752469Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for '2021-01-01' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.752651Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee consumption and mortality from all causes' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.752821Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee consumption and total mortality in mediterranean cohort' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753004Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee drinking and lower risks of mortality' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753181Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'validity of food frequency questionnaire' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753343Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'adherence to mediterranean diet and coronary heart disease risk' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753526Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'diet and overall survival in elderly people' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753701Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'adherence to mediterranean diet and survival' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.753964Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'database' in category 'classes'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.754204Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'usda national nutrient database' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.754391Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'coffee consumption and mortality meta-analysis' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:31:53.754580Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mNo close match found for 'mediterranean diet and multiple health outcomes' in category 'individuals'\u001B[0m [\u001B[0m\u001B[1m\u001B[34mOntologyAdapter\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T14:32:00.293116Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mCoroutine task started: `summarize_text`\u001B[0m [\u001B[0m\u001B[1m\u001B[34mrun_tasks(tasks: [Task], data)\u001B[0m]\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:32:00 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:32:00 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; 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"stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:32:20 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0m" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001B[92m16:32:23 - LiteLLM:INFO\u001B[0m: utils.py:2784 - \n", "LiteLLM completion() model= gpt-4o-mini; provider = openai" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[1m\n", "LiteLLM completion() model= gpt-4o-mini; provider = openai\u001B[0mQ: What are common risk factors for Type 2 Diabetes?\n", "A: ['Common risk factors for Type 2 Diabetes include obesity, physical inactivity, and poor diet. Additionally, coffee consumption may be related to lower mortality rates, which could indirectly influence diabetes risk. Participants aged 20 years and above are also considered in health metrics related to diabetes.']\n", "\n", "Q: What preventive measures reduce the risk of Hypertension?\n", "A: ['Preventive measures that reduce the risk of hypertension include moderate coffee consumption, which is linked to reduced cardiovascular disease mortality and potentially lower risks for hypertension, cholesterol issues, heart failure, and atrial fibrillation. Additionally, antioxidants may also provide a preventative effect on cardiovascular health.']\n", "\n", "Q: What symptoms indicate possible Cardiovascular Disease?\n", "A: ['Symptoms that may indicate possible Cardiovascular Disease include hypertension, heart failure, and atrial fibrillation. Additionally, high cholesterol levels can also be a sign of cardiovascular issues.']\n", "\n", "Q: What diseases are associated with Obesity?\n", "A: ['Diseases associated with obesity include cardiovascular disease (CVD) and diabetes mellitus.']\n", "\n" ] } ], "execution_count": 23 }, { "metadata": {}, "cell_type": "markdown", "source": [ "## Visualizing the Knowledge Graph\n", "\n", "Let's visualize how our ontology connects different medical concepts:" ], "id": "c60533d2423acdb0" }, { "metadata": { "ExecuteTime": { "end_time": "2025-04-09T15:25:33.512697Z", "start_time": "2025-04-09T15:25:33.471854Z" } }, "cell_type": "code", "source": [ "from cognee.api.v1.visualize import visualize_graph\n", "await visualize_graph()" ], "id": "36ee2a360f47a054", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\u001B[2m2025-04-09T15:25:33.504468Z\u001B[0m [\u001B[32m\u001B[1minfo \u001B[0m] \u001B[1mGraph visualization saved as /Users/vasilije/graph_visualization.html\u001B[0m [\u001B[0m\u001B[1m\u001B[34mcognee.shared.logging_utils\u001B[0m]\u001B[0m\n", "\u001B[2m2025-04-09T15:25:33.505762Z\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" ] }, { "data": { "text/plain": [ "'\\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n\\n \\n \\n \\n \\n \\n '" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 25 }, { "metadata": { "ExecuteTime": { "end_time": "2025-04-10T16:34:04.760472Z", "start_time": "2025-04-10T16:34:04.736095Z" } }, "cell_type": "code", "source": "", "id": "9268fa61dbc81664", "outputs": [], "execution_count": null }, { "metadata": {}, "cell_type": "markdown", "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" ], "id": "ff39326921b75273" }, { "metadata": {}, "cell_type": "code", "outputs": [], "execution_count": null, "source": "", "id": "8d2a0fe555a7bc0f" } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.6" } }, "nbformat": 4, "nbformat_minor": 5 }