With the ever-increasing utilization of natural language processing (NLP), we started to witness over the past few years a significant transformation in our interaction with legal texts. This technology has advanced the analysis and enhanced the understanding of complex legal terminology and contexts. The development of recent large language models (LLMs), particularly ChatGPT, has also introduced a revolutionary contribution to the way that legal texts can be processed and comprehended. In this paper, we present our work on a cooperative-legal question-answering LLM-based chatbot, where we developed a set of legal questions about Palestinian cooperatives, associated with their regulations and compared the auto-generated answers by the chatbot to their correspondences that are designed by a legal expert. To evaluate the proposed chatbot, we have used 50 queries generated by the legal expert and compared the answers produced by the chart to their relevance judgments. Finding demonstrated that an overall accuracy rate of 82% has been achieved when answering the queries, while exhibiting an F1 score equivalent to 79%.

翻译：随着自然语言处理（NLP）应用日益广泛，我们在过去几年中见证了与法律文本交互方式的显著变革。该技术推动了复杂法律术语与语境的分析与理解能力提升。近期大语言模型（LLM），特别是ChatGPT的发展，为法律文本的处理与理解带来了革命性贡献。本文介绍了我们基于LLM的合作社法律问答聊天机器人项目：我们围绕巴勒斯坦合作社及其相关法规开发了一系列法律问题，将聊天机器人自动生成的答案与法律专家设计的对应答案进行对比。为评估所提出的聊天机器人，我们使用法律专家生成的50个查询语句，将系统生成的答案与相关性判断进行比对。结果表明：系统在回答查询时总体准确率达到82%，F1分数为79%。