Using Machine Learning and Pattern-Based Methods for Identifying Elements in Chinese Judgment Documents of Civil Cases

Hong-Ren Lin, Wei-Zhi Liu, Chao-Lin Liu, Chieh Yang


Abstract
Providing structural information about civil cases for judgement prediction systems or recommendation systems can enhance the efficiency of the inference procedures and the justifiability of produced results. In this research, we focus on the civil cases about alimony, which is a relatively uncommon choice in current applications of artificial intelligence in law. We attempt to identify the statements for four types of legal functions in judgement documents, i.e., the pleadings of the applicants, the responses of the opposite parties, the opinions of the courts, and uses of laws to reach the final decisions. In addition, we also try to identify the conflicting issues between the plaintiffs and the defendants in the judgement documents.
Anthology ID:
2022.rocling-1.14
Volume:
Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)
Month:
November
Year:
2022
Address:
Taipei, Taiwan
Venue:
ROCLING
SIG:
Publisher:
The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Note:
Pages:
107–115
Language:
Chinese
URL:
https://aclanthology.org/2022.rocling-1.14
DOI:
Bibkey:
Cite (ACL):
Hong-Ren Lin, Wei-Zhi Liu, Chao-Lin Liu, and Chieh Yang. 2022. Using Machine Learning and Pattern-Based Methods for Identifying Elements in Chinese Judgment Documents of Civil Cases. In Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022), pages 107–115, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).
Cite (Informal):
Using Machine Learning and Pattern-Based Methods for Identifying Elements in Chinese Judgment Documents of Civil Cases (Lin et al., ROCLING 2022)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.rocling-1.14.pdf