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.

翻译：本研究探索了大型语言模型（LLMs）在食品安全领域中自动化提取与需求相关的法律内容，以及检查监管制品法律合规性的应用。随着工业4.0革新食品工业，以及《通用数据保护条例》（GDPR）重塑隐私政策与数据处理协议，监管分析与最新技术进步之间的鸿沟日益扩大。本研究旨在通过利用LLMs（即BERT和GPT模型）精准分类法律条款并自动化合规性检查来弥合这一差距。研究结果展示了令人鼓舞的效果，表明LLMs在合理的时间与财务成本内，通过减少人工工作量并提高准确率，显著增强了法律合规性与监管分析的效率。