Extracting Norms from Contracts Via ChatGPT: Opportunities and
  Challenges
Amanul Haque Munindar P. Singh
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.