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Document GraphRAG: Knowledge Graph Enhanced Retrieval Augmented Generation for Document Question Answering Within the Manufacturing Domain

A novel framework that incorporates knowledge graphs into the RAG pipeline for document question answering.

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Document GraphRAG: Knowledge Graph Enhanced Retrieval Augmented Generation for Document Question Answering Within the Manufacturing Domain

By Simon Knollmeyer, Oğuz Caymazer, Daniel GroßmannElectronics
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This study introduces Document Graph RAG (GraphRAG), a framework that enhances retrieval robustness and answer generation by incorporating knowledge graphs. The evaluation demonstrates consistent performance gains over a naive RAG baseline across both retrieval and generation metrics.

GraphRAG improves context relevance metrics, particularly for multi-hop questions.

Abstract

This study introduces Document Graph RAG (GraphRAG), a framework that enhances retrieval robustness and answer generation by incorporating knowledge graphs. The evaluation demonstrates consistent performance gains over a naive RAG baseline across both retrieval and generation metrics. GraphRAG improves context relevance metrics, particularly for multi-hop questions.

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document question answeringknowledge graph enhanced retrievalaugmented generationKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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