Knowledge GraphsFeatured
Knowledge Graphs for Grounded Retrieval
Designing, populating, and querying a knowledge graph that makes retrieval traceable and lets a model reason across more than one hop.
A knowledge graph stores facts as relationships between entities instead of rows in isolated tables. Combined with language models, it gives retrieval structure, makes answers traceable, and lets a system reason across hops. This topic explains how to design, populate, and query one without over-engineering it.
When is a graph the right store, and when is a relational database enough?
How do you populate a graph from documents without filling it with noise?
What does graph-based retrieval change compared to plain vector search?
How do you keep a graph accurate as the underlying sources change?
Designing, populating, and querying a knowledge graph that makes retrieval traceable and lets a model reason across more than one hop.