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FROM PARSED CORPORA TO SEMANTICALLY RELATED VERBS

机译:从草体公司到相关的动词

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摘要

A comprehensive repository of semantic relations between verbs is of great importance in supporting a large area of natural language applications. The aim of this paper is to automatically generate a repository of semantic relations between verb pairs using Distributional Memory (DM), a state-of-the-art framework for distributional semantics. The main idea of our method is to exploit relationships that are expressed through prepositions between a verbal and a nominal event in text to extract semantically related events. Then using these prepositions, we derive relation types including causal, temporal, comparison, and expansion. The result of our study leads to the construction of a resource for semantic relations, which consists of pairs of verbs associated with their probable arguments and significance scores based on our measures. Experimental evaluations show promising results on the task of extracting and categorising semantic relations between verbs.
机译:动词之间的语义关系的综合存储库对于支持大范围的自然语言应用非常重要。本文的目的是使用分布记忆(DM)(一种用于分布语义的最新框架)自动生成动词对之间的语义关系存储库。我们方法的主要思想是利用文本中言语和名词事件之间的介词表达的关系,以提取语义上相关的事件。然后,使用这些介词,我们得出关系类型,包括因果关系,时间关系,比较关系和扩展关系。我们的研究结果导致了语义关系资源的构建,该资源由一对动词及其可能的论据和根据我们的测度的显着性得分组成。实验评估表明,在动词之间的语义关系的提取和分类任务上,结果令人鼓舞。

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