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From Unstructured Text to GraphRAG: Building Knowledge Graphs for Better Retrieval

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This project demonstrates converting unstructured documents into a concept-based knowledge graph for Graph Retrieval Augmented Generation (GraphRAG). The process covers chunking, LLM-based concept extraction, relationship inference, and local graph construction using an open-source model, enabling more precise, explainable retrieval than vector-only RAG.

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