文章基本信息

标题：Integrated Japanese Dependency Analysis Using a Dialog Context
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作者：Yuki Ikegaya ; Yasuhiro Noguchi ; Satoru Kogure 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2007
卷号：22
期号：3
页码：291-310
DOI：10.1527/tjsai.22.291
出版社：The Japanese Society for Artificial Intelligence
摘要：This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.
关键词：natural language understanding ; dialog system ; parsing ; semantic analysis ; context analysis