How does GraphRAG leverage knowledge graph memory structures to enhance LLM outputs, and what are the specific operational factors and settings that allow for effective and responsible use of GraphRAG, particularly in addressing its limitations and optimizing performance metrics during unstructured text transformation?
I believe the best answers to your questions are addressed in section 2 of the graphrag paper as well as our statement on responsible AI here. Let us know if you have any further questions.
How does GraphRAG leverage knowledge graph memory structures to enhance LLM outputs, and what are the specific operational factors and settings that allow for effective and responsible use of GraphRAG, particularly in addressing its limitations and optimizing performance metrics during unstructured text transformation?