We investigate the effectiveness of ChatGPT in extracting norms from contracts. Norms provide a natural way to engineer multiagent systems by capturing how to govern the interactions between two or more autonomous parties. We extract norms of commitment, prohibition, authorization, and power, along with associated norm elements (the parties involved, antecedents, and consequents) from contracts. Our investigation reveals ChatGPT's effectiveness and limitations in norm extraction from contracts. ChatGPT demonstrates promising performance in norm extraction without requiring training or fine-tuning, thus obviating the need for annotated data, which is not generally available in this domain. However, we found some limitations of ChatGPT in extracting these norms that lead to incorrect norm extractions. The limitations include oversight of crucial details, hallucination, incorrect parsing of conjunctions, and empty norm elements. Enhanced norm extraction from contracts can foster the development of more transparent and trustworthy formal agent interaction specifications, thereby contributing to the improvement of multiagent systems.

研究ChatGPT在从合同中提取规范的效果。ChatGPT在提取规范方面展现了良好的性能，并且不需要训练或微调，从而避免了在该领域通常无法获得的标注数据的需求。然而，研究发现ChatGPT在提取这些规范方面存在一些限制，导致错误的规范提取。增强从合同中提取规范的能力可以促进更透明、可信赖的正式代理交互规范的发展，从而改进多代理系统。

通过ChatGPT从合同中提取规范：机遇与挑战