Syntactic text analysis without a dictionary

I. Bessmertny, A. Platonov, E. A. Poleschuk, Ma Peng-yu
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引用次数: 4

Abstract

Syntactic text analysis is a very important step of automatic text processing. The key problem is that all existing approaches are dictionary-dependent. It can be impossible to analyze all sentences because of the lack of one word in the dictionary. However even the presence of the dictionary does not resolve the phrases interpretation ambiguity. At the same time fusional languages contain enough information about the parts of speech. Particularly, the endings of nouns, adjectives, verbs and participles cannot fully indicate their case, number and face because of semantic ambiguity. Prepositions also cannot always correctly indicate the cases. This yields a variety phrase interpretation. To solving this problem sharing affixes and prepositions is proposed. However fusional languages have some disadvantages. One of this is the allowance of building phrases with random word order. It leads to increase the number of options. The paper proposes to use sentences templates with analyzed phrases for ambiguity decrease. In addition usage of affixes with prepositions for text analysis provides the basic elements of the semantic analysis without a dictionary.
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没有字典的句法文本分析
文本句法分析是文本自动处理的一个重要步骤。关键问题是所有现有的方法都依赖于字典。因为字典中缺少一个单词,就不可能分析所有的句子。然而,即使词典的存在也不能解决短语解释的歧义。同时,融合语言包含了足够的词类信息。特别是名词、形容词、动词和分词的词尾由于语义歧义,不能完全表明其格、数、面。介词也不能总是正确地指示情况。这就产生了不同的短语解释。为了解决这一问题,提出了词缀和介词共享的方法。然而,融合语言有一些缺点。其中之一是允许用随机词序构建短语。这会增加选择的数量。为了减少歧义,本文建议使用含有分析短语的句子模板。此外,词缀与介词的结合为文本分析提供了不借助词典进行语义分析的基本要素。
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