Abstract
In this paper, we study the problem of identifying the principals and accessories from the fact description with multiple defendants in a criminal case. We treat the fact descriptions as narrative texts and the defendants as roles over the narrative story. We propose to model the defendants with behavioral semantic information and statistical characteristics, then learning the importances of defendants within a learning-to-rank framework. Experimental results on a real-world dataset demonstrate the behavior analysis can effectively model the defendants’ impacts in a complex case.- Anthology ID:
- 2020.acl-main.393
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4265–4269
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.393
- DOI:
- 10.18653/v1/2020.acl-main.393
- Cite (ACL):
- Yakun Hu, Zhunchen Luo, and Wenhan Chao. 2020. Identifying Principals and Accessories in a Complex Case based on the Comprehension of Fact Description. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4265–4269, Online. Association for Computational Linguistics.
- Cite (Informal):
- Identifying Principals and Accessories in a Complex Case based on the Comprehension of Fact Description (Hu et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.acl-main.393.pdf