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Analysis of Definitions of Verbs in an Explanatory Dictionary for Automatic Extraction of Actants Based on Detection of Patterns

机译:基于模式检测的术语自动提取动词的定义分析

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Due to the importance that verbs have in language an identification of their actants (obligatory complements) is important for understanding of the meaning of sentences. Usually, the solution of this problem in natural language processing is based on machine learning approaches, which are trained on large sets of tagged texts. We show that it is possible to work with other kind of sources, i.e., explanatory dictionaries. Dictionary definitions have patterns that provide enough information for identifying actants. We develop a heuristic approach in order to obtain this information and developed an algorithm for detection of actants in texts.
机译:由于动词在语言中的重要性,识别他们的行动者(强制性补充)对于了解句子的意义,这对句子的意义很重要。通常,在自然语言处理中解决这个问题的解决方案是基于机器学习方法,这些方法受到大量标记文本的培训。我们表明,可以使用其他类型的来源,即解释性词典。词典定义具有提供足够的信息来识别识别工作人员的模式。我们开发了一种启发式方法,以获取这些信息,并开发了一种用于检测文本中的才能的算法。

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