GraphRAG (Knowledge Graph RAG)
Retrieval pattern that uses a knowledge graph as a structured backbone, often alongside vector search.
What is GraphRAG (Knowledge Graph RAG)?
GraphRAG (also called Knowledge Graph RAG) treats entities, relationships, and properties as first-class retrieval targets. It outperforms pure vector retrieval on multi-hop and relational questions — policy applicability, contract obligations, supply chain dependencies — and combines well with vector retrieval in hybrid setups. See Knowledge Graph RAG.
What is an example of GraphRAG (Knowledge Graph RAG)?
To assess supply risk, GraphRAG traverses from a product to components, facilities, suppliers, parent companies, locations, and incidents, then retrieves supporting contracts and reports for a cited answer.
How is GraphRAG (Knowledge Graph RAG) different from related concepts?
A knowledge graph is the structured data representation. GraphRAG is the retrieval-and-generation pattern that uses graph structure as part of the evidence pipeline.
What should enterprises evaluate for GraphRAG (Knowledge Graph RAG)?
- Choose queries that genuinely require relationships or multi-hop reasoning and compare against strong hybrid-search baselines.
- Measure entity resolution, path correctness, provenance, permission enforcement, answer support, latency, and update cost.
- Keep graph facts linked to source evidence and timestamps so generated claims can be verified.
Related terms
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