Show HN: Compare GraphRAG and RAG on earning call transcripts

[oryx1729]

Hi HN,

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.

[gkorland]

Nice demo! It so easy to see that Vector RAG just can't answer complex queries that are more that Sematic Search results.

We also build a similar demo based on the UFC dataset - https://github.com/FalkorDB/ufc