Going meta – Ep4: Ontology based reasoning 101

Going Meta
  • Season 1 · Episode 4 of 27
  • Length: 1 hr 11 min
  • 6,518 views
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  1. 1Meta : Cypher and SPARQL side by side, duration 1:11:20
  2. 2Meta – : Semantic search: A worked example, duration 1:08:58
  3. 3meta – : Controling the shape of your graph with SHACL, duration 1:07:19
  4. 4meta – : Ontology based reasoning 101, duration 1:11:02
  5. 5meta – : Ontology-driven Knowledge Graph construction, duration 1:02:23
  6. 6meta – : Ontology learning from graph data, duration 59:12
  7. 7meta – : Generating natural language from your knowledge graph by annotating ontologies, duration 1:03:26
  8. 8meta – : Common RDF Integration Patterns, duration 1:03:49
  9. 9Meta – : Unsupervised KG construction. Graph Observability, duration 1:02:10
  10. 10Meta – : SPARQL based integrations… and managing graph expectations, duration 1:07:39
  11. 11Meta – : Better Graph Data Quality with Graph Expectations, duration 1:02:45
  12. 12Meta – : Importing RDF data into Aura with Python + RDFLib, duration 1:07:38
  13. 13Meta – : Creating (and RDF-izing) virtual graphs over external data, duration 1:07:16
  14. 14Meta – : Taxonomy reconciliation, duration 1:07:49
  15. 15Meta – : Building a Semantic Data App with Streamlit, duration 1:07:39
  16. 16Meta – : Semantic Similarity Metrics in Taxonomies, duration 1:12:16
  17. 17Meta – : RDF-ing between OpenAI and Neo4j, duration 58:46
  18. 18Meta – : Easy Full-Graph Migrations from Triple Stores to Neo4j, duration 1:03:20
  19. 19Meta : Ontology Versioning in Neo4j, duration 1:10:18
  20. 20Meta – : A Recap, duration 1:10:42
  21. 21Meta – : Vector-based Semantic Search and Graph-based Semantic Search, duration 1:00:50
  22. 22Meta – : RAG with Knowledge Graphs, duration 1:03:30
  23. 23Meta – : Advanced RAG patterns with Knowledge Graphs, duration 1:04:01
  24. 24Meta – : KG+LLMs: Ontology driven RAG patterns, duration 1:10:48
  25. 25Meta – : LLMs for Automated KG Construction, duration 1:06:19
  26. 26Meta – : Unpicking the data.world Benchmark on the Role of KGs in LLM QA, duration 1:13:25
  27. 27Meta – : Building a Reflection Agent with LangGraph, duration 1:02:40

Episode 4 of Going Meta - a series on graphs, semantics and knowledge

Building basic inferencing with cypher on Neo4j. We will explain the basics of ontology based inferencing. And we'll do it with Cypher and vanilla Neo4j.

Resources mentioned

Cypher & GQLKnowledge graphs

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