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The Legal Argument Reasoning Task in Civil Procedure

2022-11-05 17:41:00
Leonard Bongard, Lena Held, Ivan Habernal
arXiv_CL
     
Abstract

We present a new NLP task and dataset from the domain of the U.S. civil procedure. Each instance of the dataset consists of a general introduction to the case, a particular question, and a possible solution argument, accompanied by a detailed analysis of why the argument applies in that case. Since the dataset is based on a book aimed at law students, we believe that it represents a truly complex task for benchmarking modern legal language models. Our baseline evaluation shows that fine-tuning a legal transformer provides some advantage over random baseline models, but our analysis reveals that the actual ability to infer legal arguments remains a challenging open research question.

Abstract (translated)

URL

https://arxiv.org/abs/2211.02950

PDF

https://arxiv.org/pdf/2211.02950.pdf

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