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Extracting Noun Phrases in Subject and Object Roles for Exploring Text Semantics

机译:提取主语和宾语中的名词短语以探索文本语义

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In tune with the recent developments in the automatic retrieval of text semantics, this paper is an attempt to extract one of the most fundamental semantic units from natural language text. The context is intuitively extracted from typed dependency structures basically depicting dependency relations instead of Part-Of-Speech tagged representation of the text. The dependency relations imply deep, fine grained, labeled dependencies that encode longdistance relations and passive information. Apart from the typed dependencies, the present work does not take the help of Noun phrase Chunking tool or Part of speech Taggers for the compound noun phrase extraction.
机译:为了适应文本语义自动检索的最新发展,本文试图从自然语言文本中提取最基本的语义单元之一。从类型化的依赖关系结构中直观地提取上下文,该结构基本上描述了依赖关系,而不是文本的词性标记表示。依赖关系表示对长距离关系和被动信息进行编码的深层,细粒度,带标签的依赖项。除了类型化的依存关系外,当前的工作没有借助名词短语“ Chunking”工具或词性标注器来进行复合名词短语的提取。

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