honeyandme/RAGQnASystem
本项目设计并实现了一个基于知识图谱 RAG 与大语言模型的医疗智能问答系统。系统以 DiseaseKG 医疗数据集为基础，依托 Neo4j 构建包含 4.4 万实体与 31 万关系的领域知识图谱；结合 BERT 命名实体识别与 32B 大模型意图识别，通过精确的图谱检索与受控的答案生成，有效缓解大模型在医疗场景中的幻觉问题，显著提升回答的准确性与可靠性。
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