Court Opinion Generation from Case Fact Description with Legal Basis

Authors

  • Quanzhi Li Alibaba Group
  • Qiong Zhang Alibaba Group

Keywords:

Social Welfare, Justice, Fairness and Equality

Abstract

In this study, we proposed an approach to automatically generating court view from the fact description of a legal case. This is a text-to-text natural language generation problem, and it can help the automatic legal document generation. Due to the specialty of the legal domain, our model exploits the charge and law article information in the generation process, instead of utilizing just the fact description text. The BERT model is used as the encoder and a Transformer architecture is used as decoder. To smoothly integrate these two parts together, we employ two separate optimizers for the two components during the training process. The experiments on two data sets of Chinese legal cases show that our approach outperforms other methods.

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Published

2021-05-18

How to Cite

Li, Q., & Zhang, Q. (2021). Court Opinion Generation from Case Fact Description with Legal Basis. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 14840-14848. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17742

Issue

Section

AAAI Special Track on AI for Social Impact