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Enhancing Language Models with Knowledge Graphs
This chapter explores the integration of knowledge graphs into retrieval-augmented generation (RAG) architecture, emphasizing their advantages over traditional data models. It illustrates how these graphs improve the accuracy of language model responses by providing contextual data, particularly in applications like customer support and fraud detection. The discussion also addresses the challenges organizations face in transitioning from prototype to production models to ensure reliable, relevant performance.