This is a 10-min video presenting the major capabilities and advantages of Quadro and demonstrates how to set up chatbot agent which uses a knowledge graph as a content repository and a structured source of domain knowledge. The most impressive capability demonstrated is the flowless text-to-SPARQL translation happening without human intervention in a predictable and transparent manner.
The test case: get NASA in the list of US government customers derived from marketing documents. Steps and challenges:
- “Chunky” RAG doesn’t work – no mention of “government” in the chunks referring to NASA
- Graph RAG Types 1 & 2 – there are too many chunks that mention U.S. Gov. organizations
- Graph RAG Type 3 “Graph as a database” gets it done!
The data in GraphDB:
Entity linking: <doc, schema:mentions, entity> generated with CEEL AI model
OTKG Content Hub: 1000 Docs + Schema.org Metadata (1M statements)
Wikidata Truthy (8B statements) + materialized inference (4B statements)
Download GraphDB and start building knowledge graphs for your data management practices!
