AILA: A Question Answering System in the Legal Domain

Weiyi Huang; Jiahao Jiang; Qiang Qu; Min Yang

IJCAI 2020poster0 citations

AILA: A Question Answering System in the Legal Domain

Weiyi Huang, Jiahao Jiang, Qiang Qu, Min Yang

Abstract

Question answering (QA) in the legal domain has gained increasing popularity for people to seek legal advice. However, existing QA systems struggle to comprehend the legal context and provide jurisdictionally relevant answers due to the lack of domain expertise. In this paper, we develop an Artificial Intelligence Law Assistant (AILA) for question answering in the domain of Chinese laws. AILA system automatically comprehends users' natural language queries with the help of the legal knowledge graph (KG) and provides the best matching answers for given queries. In addition, AILA provides visual cues to interpret the input queries and candidate answers based on the legal KG. Experimental results on a large-scale legal QA corpus show the effectiveness of AILA. To the best of our knowledge, AILA is the first Chinese legal QA system which integrates the domain knowledge from legal KG to comprehend the questions and answers for ranking QA pairs. AILA is available at http://bmilab.ticp.io:48478/.

Natural Language Processing: general

BibTeX

@inproceedings{ijcai2020p762,
  title     = {AILA: A Question Answering System in the Legal Domain},
  author    = {Huang, Weiyi and Jiang, Jiahao and Qu, Qiang and Yang, Min},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
               Artificial Intelligence, {IJCAI-20}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Christian Bessiere},
  pages     = {5258--5260},
  year      = {2020},
  month     = {7},
  note      = {Demos},
  doi       = {10.24963/ijcai.2020/762},
  url       = {https://doi.org/10.24963/ijcai.2020/762},
}