Ontologies, LLMs, Property Graphs – Do we really have a “Jaguar Problem”?
- Play from Intro
- Play from What is the “Jaguar Problem”? Context for the 6 claims
- Play from Inaccuracy #1: “LLMs cannot deal with lexical ambiguity without help”
- Play from Inaccuracy #2: “Feeding an ontology into the context window guarantees schema alignment”
- Play from Inaccuracy #3: “Extracted triples require zero post-processing”
- Play from Inaccuracy #4: “LLMs can run OWL reasoning (formal semantics)”
- Play from Inaccuracy #5: “LLMs perform better when prompted with RDF/OWL vs natural language”
- Play from Experimental results comparing NL vs OWL guidance
- Play from Inaccuracy #6: “This cannot be done with LPG / property graph databases”
- Play from Takeaways: Ontologies + LLMs + Property Graphs and how they *really* work together
- Play from Closing Q&A
- 1Ontology Creation with the Neo4j MCP Server
- 2Supercharging Neo4j Aura Agents with Ontologies
- 3Ontologies, LLMs, Property Graphs – Do we really have a “Jaguar Problem”?
- 4Evaluating the Quality of Ontologies
- 5Neo4j Agent Memory
- 6Validating Neo4j Graphs with SHACL
- 7Agent Skills For Creating and Using Ontologies
- 8The Graph Behind the Graph: Tracing Ontology Design Decisions
- 9Shape agent memory with ontologies
- 10Actionable Knowledge For Agents With Context Graphs
- 11Unwrapping OKF (and Season 3)
Season 03 Episode 3 of Going Meta – a Series on Semantics, Knowledge Graphs and All Things AI
Topic: Ontologies, LLMs, Property Graphs - Do we really have a "Jaguar Problem"?
Resources mentioned
GenAI & GraphRAGKnowledge graphs


