This research explores the application of Large Language Models (LLMs) for
automating the extraction of requirement-related legal content in the food
safety domain and checking legal compliance of regulatory artifacts. With
Industry 4.0 revolutionizing the food industry and with the General Data
Protection Regulation (GDPR) reshaping privacy policies and data processing
agreements, there is a growing gap between regulatory analysis and recent
technological advancements. This study aims to bridge this gap by leveraging
LLMs, namely BERT and GPT models, to accurately classify legal provisions and
automate compliance checks. Our findings demonstrate promising results,
indicating LLMs' significant potential to enhance legal compliance and
regulatory analysis efficiency, notably by reducing manual workload and
improving accuracy within reasonable time and financial constraints.

研究探索了利用大型语言模型（LLMs）自动提取食品安全领域与要求相关的法律内容并检查法规工件的合规性。研究结果表明，LLMs 在提高法规合规性和监管分析效率方面具有显著的潜力，尤其通过减少手动工作量，提高准确性，并在合理的时间和财务限制下实现。