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Automatic Syntactic Segment Filtration for Mass Syntax Corpus with Mutual Information

机译:具有相互信息的大规模语法语料库自动句法段过滤

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Syntactic analysis (Syntactic parsing) is an important method in the natural language processing. The Syntactic parsing aims to find a linguistic structure of a sentence with the knowledge of a certain grammar. The constituent parser which can build hierarchical structure with the phrase segments is the most popular method in nowadays NLP applications. Many approaches have been done to the parsing algorithms to improve the precision and recall of the found syntactic segments. In this paper, we propose a novel method to greatly improve the precision of the syntactic segments without dig into the parsing algorithms. The method is introduced as a post-processing which filters the syntactic segments according to their mutual information with the context. The new method can obtain a high confidential subset from a mass syntax corpus and is independent with the parsing algorithms. The effectiveness of the approach is validated by the experimental results.
机译:语法分析(句法解析)是自然语言处理中的重要方法。句法解析旨在找到一种句子的语言结构,了解某种语法的知识。可以使用短语段构建分层结构的组成解析器是如今NLP应用中最受欢迎的方法。已经对解析算法进行了许多方法,以改善发现的句法段的精度和召回。在本文中,我们提出了一种新颖的方法,可以大大提高语法片段的精度,而不挖掘解析算法。该方法被引入作为与上下文相互信息过滤句法段的后处理。新方法可以从质量语法语料库中获得高机密子集,并且与解析算法无关。该方法的有效性由实验结果验证。

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