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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:基于模式检测的动词自动提取解释性词典中动词的定义分析

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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:由于动词在语言中具有重要意义,因此,对其动词的识别(强制性补语)对于理解句子的意义非常重要。通常,在自然语言处理中解决此问题的方法是基于机器学习方法,该方法在大量标记文本上进行训练。我们表明可以与其他种类的资料,即解释性词典一起使用。字典定义的模式可提供足够的信息来识别参与者。为了获得此信息,我们开发了一种启发式方法,并开发了一种用于检测文本中的参与者的算法。

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