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Exploring Both Flat and Structured Features for Number Type Identification of Chinese Personal Noun Phrases

机译:探索扁平和结构化特征,用于数字类型识别中国个人名词短语

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Different from English, Chinese does not explicitly show grammatical number information by inflection. The Number information in a Chinese sentence is implied by the noun phrase itself and its surrounding context. In this paper, we explore diverse features, including both flat and structured, for number identification of Chinese personal noun phrase. The flat features explore the knowledge within the noun phrase while the structured features capture the surrounding context information of the noun phrase in the parse tree of the given sentence. These two kinds of features together with kernel-based SVM are utilized in this study. Evaluation on the ACE 2005 corpus shows that our method achieves 89.23% in accuracy, which significantly advances the state-of-the-art.
机译:与英语不同,中文没有明确地通过拐点显示语法编号信息。 noun短语本身及其周围背景暗示了汉语句子的数字信息。在本文中,我们探讨了不同的功能,包括平板和结构,用于中国个人名词短语的数量识别。平面特征在结构化特征捕获给定句子的解析树中捕获Noun短语的周围上下文信息,探讨了名词短语中的知识。本研究中使用了这两种特征与基于内核的SVM一起使用。 ACE 2005语料库的评估表明,我们的方法以准确性实现了89.23%,这显着推进了最先进的。

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