目的 利用知识图谱的语义信息和结构化优势，构建基于食品安全标准及HACCP规范的知识图谱问答系统可为全产业链的食品安全控制提供精准、快速的问题解答。方法 在从多个数据源中获得大量食品安全标准及HACCP规范文件的基础上，利用知识图谱技术(Knowledge Graph，KG)进行信息提取及层次分析，将数据存储在Neo4j中，采用Flask Web框架构建食品安全标准及HACCP规范的知识图谱问答系统。结果 以肉类全产业链的食品安全管控为例，实现了对肉制品全链条的安全标准及推荐的关键控制点(Critical Control Point，CCP)信息的知识问答可视化。结论 研究可为企业进行食品安全风险的精准防控提供参考依据。

The work aims to construct the Knowledge Graph-Based Question-Answering System for Food Safety Standards and HACCP Guidelines by leveraging the semantic information and structured advantages of knowledge graphs, so as to provide accurate and rapid answers for food safety control across the supply chain. On the basis of obtaining a large number of food safety standards and HACCP guideline documents from multiple data sources, information extraction and hierarchical analysis were performed by knowledge graph technology (Knowledge Graph, KG), with data imported into Neo4j. The Knowledge Graph-Based Question-Answering System for Food Safety Standards and HACCP Guidelines was built by the Flask web framework. With the food safety management and control of meat products as an example, the visualization of knowledge queries related to safety standards and recommending critical control points was achieved. This study provides a reference basis for the precise control of food safety risks in the future.