Analyzable Legal Yes/No Question Answering System using Linguistic Structures

11 pages•Published: June 3, 2017

Yoshinobu Kano, Reina Hoshino and Ryosuke Taniguchi

Abstract

A central issue of yes/no question answering is usage of knowledge source given a question. While yes/no question answering has been studied for a long time, legal yes/no question answering largely differs from other domains. The most distinguishing characteristic is that legal issues require precise linguistic analysis such as predicates, case-roles, conditions, etc. We have developed a yes/no question answer-ing system for answering questions in a legal domain. Our system uses linguistic analysis, in order to find correspondences of predicates and arguments given problem sentences and knowledge source sentences. We applied our system to the COLIEE (Competition on Legal Information Extraction/Entailment) 2017 task. Our team shared the second place in this COLIEE 2017 Phase Two task, which asks to answer yes or no given a problem sentence. This result shows that precise linguistic analyses are effective even without the big data approach with machine learning, rather better in its analyzable design for future improvements.

Keyphrases: coliee, legal document processing, natural language processing, yes/no question answering

In: Ken Satoh, Mi-Young Kim, Yoshinobu Kano, Randy Goebel and Tiago Oliveira (editors). COLIEE 2017. 4th Competition on Legal Information Extraction and Entailment, vol 47, pages 57-67.

Links:	https://easychair.org/publications/paper/zdP
	https://doi.org/10.29007/16q5

BibTeX entry

@inproceedings{COLIEE2017:Analyzable_Legal_Yes/No_Question,
  author    = {Yoshinobu Kano and Reina Hoshino and Ryosuke Taniguchi},
  title     = {Analyzable Legal Yes/No Question Answering System using Linguistic Structures},
  booktitle = {COLIEE 2017. 4th Competition on Legal Information Extraction and Entailment},
  editor    = {Ken Satoh and Mi-Young Kim and Yoshinobu Kano and Randy Goebel and Tiago Oliveira},
  series    = {EPiC Series in Computing},
  volume    = {47},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/zdP},
  doi       = {10.29007/16q5},
  pages     = {57-67},
  year      = {2017}}

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