research-article

Legal Judgment Elements Extraction Approach with Law Article-aware Mechanism

Authors:

Ru LiAuthors Info & Claims

Transactions on Asian and Low-Resource Language Information Processing, Volume 21, Issue 3

Article No.: 55, Pages 1 - 15

https://doi.org/10.1145/3485244

Published: 21 December 2021 Publication History

Abstract

Legal judgment elements extraction (LJEE) aims to identify the different judgment features from the fact description in legal documents automatically, which helps to improve the accuracy and interpretability of the judgment results. In real court rulings, judges usually need to scan both the fact descriptions and the law articles repeatedly to find out the relevant information, and it is hard to acquire the key judgment features quickly, so legal judgment elements extraction is a crucial and challenging task for legal judgment prediction. However, most existing methods follow the text classification framework, which fails to model the attentive relations of the law articles and the legal judgment elements. To address this issue, we simulate the working process of human judges, and propose a legal judgment elements extraction method with a law article-aware mechanism, which captures the complex semantic correlations of the law article and the legal judgment elements. Experimental results show that our proposed method achieves significant improvements than other state-of-the-art baselines on the element recognition task dataset. Compared with the BERT-CNN model, the proposed “All labels Law Articles Embedding Model (ALEM)” improves the accuracy, recall, and F1 value by 0.5, 1.4 and 1.0, respectively.

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Cited By

Bozdag MSevim NKoç A(2024)Measuring and Mitigating Gender Bias in Legal Contextualized Language ModelsACM Transactions on Knowledge Discovery from Data10.1145/362860218:4(1-26)Online publication date: 13-Feb-2024
https://dl.acm.org/doi/10.1145/3628602
Pan WChen YLiu ZLi XXu Z(2023)Circumstance-Aware Graph Neural Network for Legal Judgment Prediction2023 International Conference on Asian Language Processing (IALP)10.1109/IALP61005.2023.10337257(332-337)Online publication date: 18-Nov-2023
https://doi.org/10.1109/IALP61005.2023.10337257
Vidler TMcGarry KBaglee D(2023)Text Mining Legal Documents for Clause Extraction2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)10.1109/CSCE60160.2023.00243(1469-1476)Online publication date: 24-Jul-2023
https://doi.org/10.1109/CSCE60160.2023.00243
Show More Cited By

Index Terms

Legal Judgment Elements Extraction Approach with Law Article-aware Mechanism
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 21, Issue 3

May 2022

413 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3505182

Editor:
Imed Zitouni
Google, USA

Issue’s Table of Contents

ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 December 2021

Accepted: 01 September 2021

Revised: 01 June 2021

Received: 01 March 2020

Published in TALLIP Volume 21, Issue 3

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National Natural Science Fund of China
National Social Science Fund of China
Natural Science Foundation of Shanxi Province

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Cited By

Bozdag MSevim NKoç A(2024)Measuring and Mitigating Gender Bias in Legal Contextualized Language ModelsACM Transactions on Knowledge Discovery from Data10.1145/362860218:4(1-26)Online publication date: 13-Feb-2024
https://dl.acm.org/doi/10.1145/3628602
Pan WChen YLiu ZLi XXu Z(2023)Circumstance-Aware Graph Neural Network for Legal Judgment Prediction2023 International Conference on Asian Language Processing (IALP)10.1109/IALP61005.2023.10337257(332-337)Online publication date: 18-Nov-2023
https://doi.org/10.1109/IALP61005.2023.10337257
Vidler TMcGarry KBaglee D(2023)Text Mining Legal Documents for Clause Extraction2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)10.1109/CSCE60160.2023.00243(1469-1476)Online publication date: 24-Jul-2023
https://doi.org/10.1109/CSCE60160.2023.00243
Zhao GLiu YTan WWang J(2023)Legal Elements Extraction via Label Recross Attention and Contrastive Learning2023 IEEE 6th International Conference on Big Data and Artificial Intelligence (BDAI)10.1109/BDAI59165.2023.10256817(73-78)Online publication date: 7-Jul-2023
https://doi.org/10.1109/BDAI59165.2023.10256817

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