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Semantic Classification of Automatically Acquired Nouns using Lexico-Syntactic Clues

机译:Lexico句法线索对自动获取名词的语义分类

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摘要

In this paper, we present a two-stage ap-proach to acquire Japanese unknown mor-phemes from text with full POS tags as-signed to them. We first acquire unknown morphemes only making a morphology-level distinction, and then apply semantic classification to acquired nouns. One ad-vantage of this approach is that, at the sec-ond stage, we can exploit syntactic clues in addition to morphological ones because as a result of the first stage acquisition, we can rely on automatic parsing. Japanese semantic classification poses an interest-ing challenge: proper nouns need to be distinguished from common nouns. It is because Japanese has no orthographic distinction between common and proper nouns and no apparent morphosyntactic distinction between them. We explore lexico-syntactic clues that are extracted from automatically parsed text and inves-tigate their effects.
机译:在本文中,我们提出了一种分两步的方法,从带有完整POS标签的文本中获取日语未知词素。我们首先获取仅进行形态学级别区分的未知语素,然后将语义分类应用于所获取的名词。这种方法的一个优点是,在第二阶段,我们可以利用语法线索,除了形态线索之外,因为第一阶段的获取,我们可以依靠自动解析。日语语义分类带来了一个有趣的挑战:专有名词需要与普通名词区分开。这是因为日语在普通名词和专有名词之间没有拼字法上的区别,在它们之间也没有明显的形态句法上的区别。我们探索从自动解析的文本中提取的词汇句法线索,并研究其效果。

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