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.