Microsoft recently open-sourced the GraphRAG framework for information retrieval, utilizing graph-based structures. It automates the construction of knowledge graphs using LLMs and enhances retrieval by connecting related concepts and entities in a query for more contextual and accurate responses.
GraphRAG offers a larger connected context for retrieved information, which LLMs use to answer summarization-focused queries. It does not replace RAG but can significantly augment existing information extraction pipelines.
Asking questions on financial data is one example of a great use case for GraphRAG.
Check out this demo comparing quarterly earnings call transcripts from a few companies to see a side-by-side comparison: https://graphrag-demo.deepset.ai
Curious to hear your thoughts.
Show HN: Compare GraphRAG and RAG on earning call transcripts
graphrag-demo.deepset.ai