Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing

被引:0
作者
Yamamoto, Yuki [1 ]
Matsumoto, Yuji [2 ]
Watanabe, Taro [1 ]
机构
[1] Nara Inst Sci & Technol, Ikoma, Nara, Japan
[2] RIKEN Ctr Adv Intelligence Project, Tokyo, Japan
来源
10TH CONFERENCE ON LEXICAL AND COMPUTATIONAL SEMANTICS (SEM 2021) | 2021年
关键词
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Meaning Representation (AMR) is a sentence-level meaning representation based on predicate argument structure. One of the challengeswe find inAMRparsing is to capture the structure of complex sentences which expresses the relation between predicates. Knowing the core part of the sentence structure in advance may be beneficial in such a task. In this paper, we present a list of dependency patterns for English complex sentence constructions designed forAMRparsing. With a dedicated pattern matcher, all occurrences of complex sentence constructions are retrieved from an input sentence. While some of the subordinators have semantic ambiguities, we deal with this problem through training classification models on data derived from AMR and Wikipedia corpus, establishing a new baseline for future works. The developed complex sentence patterns and the corresponding AMR descriptions will be made public(1).
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收藏
页码:212 / 221
页数:10
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