Legal Prompt Engineering (LPE) or Legal Prompting is a process to guide and assist a large language model (LLM) with performing a natural legal language processing (NLLP) skill. Our goal is to use LPE with LLMs over long legal documents for the Legal Judgement Prediction (LJP) task. We investigate the performance of zero-shot LPE for given facts in case-texts from the European Court of Human Rights (in English) and the Federal Supreme Court of Switzerland (in German, French and Italian). Our results show that zero-shot LPE is better compared to the baselines, but it still falls short compared to current state of the art supervised approaches. Nevertheless, the results are important, since there was 1) no explicit domain-specific data used - so we show that the transfer to the legal domain is possible for general-purpose LLMs, and 2) the LLMs where directly applied without any further training or fine-tuning - which in turn saves immensely in terms of additional computational costs.
翻译:法律即时工程(LPE)或法律提示(LPE)是一个指导和协助大型语言模型(LLM)进行自然法律语言处理(NLLP)技能的过程。我们的目标是在法律判决预测(LJP)任务的长期法律文件上使用LPE与LLMs使用LPE与LLMs的长篇法律文件。我们调查欧洲人权法院(英文)和瑞士联邦最高法院(德文、法文和意大利文)案例文本中特定事实的零射LPE的性能。我们的结果显示,零射LPE比基线好,但与目前艺术监督方法的状态相比,它仍然不足。然而,结果很重要,因为没有使用明确的特定领域数据――因此我们表明,一般用途LLMS可以转让到法律领域,2 直接应用的LLMMS不经过任何进一步培训或微调,这反过来又大大节省了额外的计算费用。