Text-guided Legal Knowledge Graph Reasoning

• URL: http://arxiv.org/abs/2104.02284v1
• Date: Tue, 6 Apr 2021 04:42:56 GMT
• Title: Text-guided Legal Knowledge Graph Reasoning
• Authors: Luoqiu Li, Zhen Bi, Hongbin Ye, Shumin Deng, Hui Chen, Huaixiao Tou, Ningyu Zhang, Huajun Chen
• Abstract summary: We propose a novel legal application of legal provision prediction (LPP), which aims to predict the related legal provisions of affairs. We collect amounts of real-world legal provision data from the Guangdong government service website and construct a legal dataset called LegalLPP.
• Score: 11.089663225933412
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent years have witnessed the prosperity of legal artificial intelligence with the development of technologies. In this paper, we propose a novel legal application of legal provision prediction (LPP), which aims to predict the related legal provisions of affairs. We formulate this task as a challenging knowledge graph completion problem, which requires not only text understanding but also graph reasoning. To this end, we propose a novel text-guided graph reasoning approach. We collect amounts of real-world legal provision data from the Guangdong government service website and construct a legal dataset called LegalLPP. Extensive experimental results on the dataset show that our approach achieves better performance compared with baselines. The code and dataset are available in \url{https://github.com/zjunlp/LegalPP} for reproducibility.

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