ModelRefs / GraphRAG — AI Glossary
GraphRAG — AI Glossary
A RAG variant that retrieves over a knowledge graph — enabling global summary queries that pure vector search cannot answer.
Overview
GraphRAG (Microsoft Research, 2024) clusters documents into entity communities and builds a hierarchical graph. Queries can then use community summaries to answer holistic questions like 'What are the main themes in this corpus?' Vector RAG handles local factual retrieval better.
Reference details
| Topic | rag |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
Retrieves over an entity graph rather than a flat set of chunks, which lets it answer questions no top-k similarity search can: global questions about themes across a whole corpus, and multi-hop questions connecting entities that never co-occur in one chunk. The cost is an extraction and graph-construction step over the corpus up front, so it is not a drop-in change to an existing pipeline.
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Frequently asked questions
What is GraphRAG?
A RAG variant that retrieves over a knowledge graph — enabling global summary queries that pure vector search cannot answer.
What concepts are related to GraphRAG?
Closely related concepts include rag, knowledge graph, embedding.