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2020 | OriginalPaper | Chapter

Multi-task Legal Judgement Prediction Combining a Subtask of the Seriousness of Charges

Authors : Zhuopeng Xu, Xia Li, Yinlin Li, Zihan Wang, Yujie Fanxu, Xiaoyan Lai

Published in: Chinese Computational Linguistics

Publisher: Springer International Publishing

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Abstract

Legal Judgement Prediction has attracted more and more attention in recent years. One of the challenges is how to design a model with better interpretable prediction results. Previous studies have proposed different interpretable models based on the generation of court views and the extraction of charge keywords. Different from previous work, we propose a multi-task legal judgement prediction model which combines a subtask of the seriousness of charges. By introducing this subtask, our model can capture the attention weights of different terms of penalty corresponding to charges and give more attention to the correct terms of penalty in the fact descriptions. Meanwhile, our model also incorporates the position of defendant making it capable of giving attention to the contextual information of the defendant. We carry several experiments on the public CAIL2018 dataset. Experimental results show that our model achieves better or comparable performance on three subtasks compared with the baseline models. Moreover, we also analyze the interpretable contribution of our model.

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Footnotes
Literature
1.
Chen, H., Cai, D., Dai, W., Dai, Z., Ding, Y.: Charge-based prison term prediction with deep gating network. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pp. 6361–6366 (2019)
2.
Hu, Z., Li, X., Tu, C., Liu, Z., Sun, M.: Few-shot charge prediction with discriminative legal attributes. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 487–498 (2018)
3.
Katz, D.M., Bommarito Ii, M.J., Blackman, J.: Predicting the behavior of the supreme court of the united states: A general approach. Plos One 12(4) (2014)
4.
Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1746–1751 (2014)
5.
Li, Z., Sun, M.: Punctuation as implicit annotations for Chinese word segmentation (2009)
6.
Lin, W.C., Kuo, T.T., Chang, T.J., Yen, C.A., Chen, C.J., Lin, S.D.: Exploiting machine learning models for Chinese legal documents labeling, case classification, and sentencing prediction in Chinese. In: Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012), pp. 140–141 (2012)
7.
Liu, C.L., Hsieh, C.D.: Exploring phrase-based classification of judicial documents for criminal charges in Chinese. In: Foundations of Intelligent Systems, pp. 681–690 (2006)
8.
Liu, Y., Chen, Y., Ho, W.: Predicting associated statutes for legal problems. Inf. Process. Manag. 51(1), 194–211 (2015)CrossRef
9.
Liu, Z., Zhang, M., Zhen, R., Gong, Z., Yu, N., Fu, G.: Multi-task learning model for legal judgment predictions with charge keywords. J. Tsinghua Univ. (Sci. Technol.) 59(7), 497 (2019)
10.
Luo, B., Feng, Y., Xu, J., Zhang, X., Zhao, D.: Learning to predict charges for criminal cases with legal basis. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2727–2736 (2017)
11.
Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. Computer Science (2013)
12.
Wang, W., Chen, Y., Cai, H., Zeng, Y., Yang, H.: Judicial document intellectual processing using hybrid deep neural networks. J. Tsinghua Univ. (Sci. Technol.) 59(7), 505 (2019)
13.
14.
15.
Yang, W., Jia, W., Zhou, X., Luo, Y.: Legal judgment prediction via multi-perspective bi-feedback network. In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, pp. 4085–4091 (2019)
16.
Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1480–1489 (2016)
17.
Ye, H., Jiang, X., Luo, Z., Chao, W.: Interpretable charge predictions for criminal cases: Learning to generate court views from fact descriptions. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1854–1864 (2018)
18.
Zhong, H., Guo, Z., Tu, C., Xiao, C., Liu, Z., Sun, M.: Legal judgment prediction via topological learning. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3540–3549 (2018)
19.
Zhong, H., Wang, Y., Tu, C., Zhang, T., Liu, Z., Sun, M.: Iteratively questioning and answering for interpretable legal judgment prediction. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 1250–1257 (2020)
Metadata
Title
Multi-task Legal Judgement Prediction Combining a Subtask of the Seriousness of Charges
Authors
Zhuopeng Xu
Xia Li
Yinlin Li
Zihan Wang
Yujie Fanxu
Xiaoyan Lai
Copyright Year
2020
Book
Chinese Computational Linguistics

Print ISBN: 978-3-030-63030-0

Electronic ISBN: 978-3-030-63031-7

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-63031-7_30

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