Pairing LLMs with structured ontologies creates a verification layer that catches errors and enables long-term memory—turning language models into more reliable reasoning systems for planning and decision-making.
This paper proposes adding a structured knowledge graph layer to LLMs using RDF/OWL ontologies, enabling persistent memory and verifiable reasoning. The system automatically builds ontologies from documents and APIs, then combines graph-based reasoning with LLM inference to improve multi-step planning tasks and add formal validation to AI outputs.