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A minimal guide to using OWL ontologies to ground Cognee’s knowledge graphs. The guide uses remember() so the data and ontology config are processed together in one call. Before you start:
  • Complete Quickstart to understand basic operations
  • Read Ontologies to understand the concepts
  • Ensure you have LLM Providers configured
  • Have an OWL ontology file (.owl) in RDF/XML format
  • Have some text or files relevant to the ontology’s domain

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What Ontology Support Does

  • Grounds entities and relations to your OWL ontology (classes, individuals, properties)
  • Validates types via ontology domains/ranges and class hierarchy
  • Improves graph completion answers for domain-specific queries

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Step 1: Prepare an Ontology File

Start from a simple OWL file. Minimal ingredients:
  • Classes (e.g., TechnologyCompany, Car)
  • Individuals (e.g., Apple, Audi)
  • Object properties with domain/range (e.g., produces with domain=CarManufacturer, range=Car)
Example ontology files:
  • examples/guides/ontology_input_example/basic_ontology.owl (GitHub)
Use any RDF/OWL editor (Protégé) to edit .owl files.
This example uses a simple ontology for demonstration. In practice, you can work with larger, more complex ontologies - the same approach works regardless of ontology size or complexity.

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Step 2: Prepare Your Data

Add either raw text or a directory. Keep it relevant to your ontology. 
texts = [
    "Audi produces the R8 and e-tron.",
    "Apple develops iPhone and MacBook."
]
This simple example uses a list of strings for demonstration. In practice, you can add multiple documents, files, or entire datasets - the ontology processing works the same way across all your data.

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Step 3: Remember Your Data with the Ontology Config

Create the config that contains the ontology information, then pass it directly to remember(). 
# Create full config structure manually
config: Config = {
    "ontology_config": {
        "ontology_resolver": RDFLibOntologyResolver(ontology_file=ontology_path)
    }
}

await cognee.remember(texts, config=config, self_improvement=False)
If omitted, Cognee builds memory without ontology grounding. With an ontology config, Cognee aligns nodes to classes and individuals while processing the remembered data.

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Hot Reload and File Updates

Ontology files are parsed once at initialization — when RDFLibOntologyResolver is constructed, it reads and parses the file with RDFLib and caches the result in memory. There is no automatic file system monitoring, so changes to the .owl file on disk are not picked up while a session or server is running.

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Full Example

import asyncio
import cognee
import os
from cognee.modules.ontology.ontology_config import Config
from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver


async def main():
    # Prune data and system metadata before running, only if we want "fresh" state.
    await cognee.prune.prune_data()
    await cognee.prune.prune_system(metadata=True)

    texts = ["Audi produces the R8 and e-tron.", "Apple develops iPhone and MacBook."]

    ontology_path = os.path.join(
        os.path.dirname(os.path.abspath(__file__)), "ontology_input_example/basic_ontology.owl"
    )

    # Create full config structure manually
    config: Config = {
        "ontology_config": {
            "ontology_resolver": RDFLibOntologyResolver(ontology_file=ontology_path)
        }
    }

    await cognee.remember(texts, config=config, self_improvement=False)


if __name__ == "__main__":
    asyncio.run(main())

import cognee
import os
from cognee.modules.ontology.ontology_config import Config
from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver

ontology_path = os.path.join(
    os.path.dirname(os.path.abspath(__file__)), "ontology_input_example/basic_ontology.owl"
)

# Create full config structure manually
config: Config = {
    "ontology_config": {
        "ontology_resolver": RDFLibOntologyResolver(ontology_file=ontology_path)
    }
}

await cognee.cognify(config=config)
  • Basic ontology demo script can be found on the following link
  • Advanced ontology demo script can be found on the following link

Core Concepts

Understand ontology fundamentals

API Reference

Explore ontology API endpoints