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.

本研究使用 Legal Prompt Engineering 作为辅助工具，对长篇法律文件进行识别和理解，以进行法律判决预测任务。在人权法庭和瑞士联邦最高法院的案例中，无需领域特定的数据和额外的计算成本，只使用通用语言模型。结果显示，零 - shot LPE 相比基准方法表现更好，表明通用 LLMs 可能具有向法律领域的跨领域能力。