Crafting a Neo4j Knowledge Graph Semantic Reasoner for LPG-Based Ontologies with Python and CDC
summary
A Neo4j-based semantic reasoner is constructed with Python that maps LPG structures to RDF/OWL, generates Cypher rules from an RDF ontology, and applies them until convergence — here reached after three iterations for the demo. CDC is enabled to stream updates and a running server applies CDC-driven incremental inference so Kevin Bacon numbers and co-actor edges update on the fly. The demo includes runnable scripts, a server, and a GitHub repo, and shows the approach works end to end.
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chapters (18)
- 0:00Introduction
- 1:14LPG model overview
- 3:25Problem statement
- 3:46RDF and RDF star
- 5:58LPG with RDF approach
- 7:02Movie graph demo
- 10:15RDF ontology design
- 13:49Movie graph ontology
- 15:14Loading ontology graph
- 16:42Inferring LPG graph
- 18:31Inference on movie graph
- 19:15Infer to convergence
- 21:27Change data capture
- 22:32CDC activation
- 23:56Running inference server
- 24:16Dynamic inference demo
- 25:00Summary and insights
- 26:14Q&A and closing
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