Context graphs fix RAG's blind spot: attaching time, audience and provenance to retrieved evidence
JeremyCMorgan · x · 2026-11-10
Jeremy Morgan highlights Datafortune's GraphRAG explainer: standard RAG can retrieve the right document yet still answer wrongly if the source is outdated, because it drops the invisible labels of "when it applies, to whom, and on whose authority."
- Core idea: a context graph interprets questions, filters retrieved evidence, and attaches provenance, restoring the labels plain RAG strips off.
- The Retrieval Relay, three handoffs: before retrieval the graph reads the question; during retrieval RAG finds text while the graph connects it; after retrieval the graph attaches the proof.
- Evidence: Microsoft Research's GraphRAG study reports substantial gains in comprehensiveness and diversity of answers on questions spanning large private datasets.
Especially relevant for compliance- and policy-heavy enterprise AI systems.
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