eagerlearners at SemEval2024 Task 5: The Legal Argument Reasoning Task in Civil Procedure

• URL: http://arxiv.org/abs/2406.16490v1
• Date: Mon, 24 Jun 2024 09:57:44 GMT
• Title: eagerlearners at SemEval2024 Task 5: The Legal Argument Reasoning Task in Civil Procedure
• Authors: Hoorieh Sabzevari, Mohammadmostafa Rostamkhani, Sauleh Eetemadi,
• Abstract summary: This study investigates the performance of the zero-shot method in classifying data using three large language models. Our main dataset comes from the domain of U.S. civil procedure.
• Score: 0.04096453902709291
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This study investigates the performance of the zero-shot method in classifying data using three large language models, alongside two models with large input token sizes and the two pre-trained models on legal data. Our main dataset comes from the domain of U.S. civil procedure. It includes summaries of legal cases, specific questions, potential answers, and detailed explanations for why each solution is relevant, all sourced from a book aimed at law students. By comparing different methods, we aimed to understand how effectively they handle the complexities found in legal datasets. Our findings show how well the zero-shot method of large language models can understand complicated data. We achieved our highest F1 score of 64% in these experiments.

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