GraphRAG - Using Knowledge Graphs to Empower LLMs

LLM-generated knowledge graph built from a private dataset using GPT-4 Turbo (Microsoft, 2024)

Back in the 1980s, I did my PhD in AI using Sowa's Conceptual Graphs, what we would now refer to as knowledge graphs. We've known for a while that providing LLMs with specific knowledge in the form of RAGs improves their accuracy. However, we've experimented with providing knowledge to LLMs in more explicit formats, for example, as cases in case-based reasoning augmented RAGs. Now, Microsoft has announced  GraphRAG, its Knowledge Graph-augmented LLM tool. The interesting thing about GraphRAG is that the knowledge graph is created by an LLM before being used to guide the LLM's retrieval. The LLM is, therefore, bootstrapping itself and "By using the LLM-generated knowledge graph, GraphRAG vastly improves the “retrieval” portion of RAG, populating the context window with higher relevance content, resulting in better answers and capturing evidence provenance."

Read Microsoft's announcement GraphRAG: Unlocking LLM discovery on narrative private data. For more information about the GraphRAG project, watch this video.