A bit of a context generated from a video on YouTube:
- Graph RAG demonstrates substantial improvements in answering two classes of questions:
- Connecting disparate pieces of information through shared attributes to provide new synthesized insights.
- Holistically understanding summarized semantic concepts over large data collections or singular larger documents.
- Graph RAG outperforms baseline RAG approaches in scenarios where the baseline struggles, such as connecting the dots or understanding semantic concepts across large data sets.
- The knowledge graph created by the LLM allows it to ground itself and provide superior answers with provenance and links to supporting text from the original data.