Going Meta – Ep 25: LLMs for Automated KG Construction

Going Meta
  • Season 1 · Episode 25 of 27
  • Length: 1 hr 6 min
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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 25 of Going Meta – a series on graphs, semantics and knowledge

Check out community.neo4j.com (opens in a new tab) for questions and discussions around Neo4j.

0:00 Intro
5:23 Graph Jokes
9:55 LLMs for Automated KG Construction
19:25 Demo #1 Housing Market
37:10 Demo #2 Supply Chain
52.50 Q&A
1:04:33 Wrap-Up

Resources mentioned

GenAI & GraphRAGKnowledge graphsAuraDB

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