An Empirical Evaluation of AMR Parsing for Legal Documents

被引：0
|
作者：
Trong Sinh Vu [1 ]
Le Minh Nguyen [1 ]
机构：
[1] Japan Adv Inst Sci & Technol JAIST, Nomi, Japan
来源：
NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE (JSAI-ISAI 2018) | 2019年 / 11717卷
关键词：
Abstract Meaning Representation; Semantic parsing; Legal text;
D O I：
10.1007/978-3-030-31605-1_11
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Many approaches have been proposed to tackle the problem of Abstract Meaning Representation (AMR) parsing, help solving various natural language processing issues recently. In our paper, we provide an overview of different methods in AMR parsing and their performances when analyzing legal documents. We conduct experiments of different AMR parsers on our annotated dataset extracted from the English version of Japanese Civil Code. Our results show the limitations as well as open a room for improvements of current parsing techniques when applying in this non-trivial domain.
引用
收藏
页码：131 / 145
页数：15
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