Project GraphRAG
LLM-Derived Knowledge Graphs
GraphRAG
GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM prompting and summarization into a single end-to-end system.
-
GraphRAG: Unlocking LLM discovery on narrative private data
2024年2月13日 | Jonathan Larson, Steven Truitt
-
GraphRAG: New tool for complex data discovery now on GitHub
2024年7月2日 | Darren Edge, Ha Trinh, Steven Truitt, Jonathan Larson
-
GraphRAG: Improving global search via dynamic community selection
2024年11月15日 | Bryan Li, Ha Trinh, Darren Edge, Jonathan Larson
-
LazyGraphRAG: Setting a new standard for quality and cost
2024年11月25日 | Darren Edge, Ha Trinh, Jonathan Larson
-
Moving to GraphRAG 1.0 – Streamlining ergonomics for developers and users
2024年12月16日 | Nathan Evans, Alonso Guevara Fernández, Joshua Bradley
-
Claimify: Extracting high-quality claims from language model outputs
2025年3月19日 | Dasha Metropolitansky
-
BenchmarkQED: Automated benchmarking of RAG systems
2025年6月5日 | Darren Edge, Ha Trinh, Andres Morales Esquivel, Jonathan Larson
-
VeriTrail: Detecting hallucination and tracing provenance in multi-step AI workflows
2025年8月5日 | Dasha Metropolitansky
Microsoft Discovery
GraphRAG and LazyGraphRAG technology is now available through Microsoft Discovery (opens in new tab), an agentic platform for scientific research built in Azure.