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Identification of Maximal-Length Noun Phrases Based on Expanded Chunks and Classified Punctuations in Chinese  

Bai, Xue-Mei ((주)4U Applications)
Li, Jin-Ji (포항공과대학교 컴퓨터공학과)
Kim, Dong-Il (연변과학기술대학교 컴퓨터전자통신학부)
Lee, Jong-Hyeok (포항공과대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.4, 2009 , pp. 320-328 More about this Journal
Abstract
In general, there are two types of noun phrases(NP): Base Noun Phrase(BNP), and Maximal-Length Noun Phrase(MNP). MNP identification can largely reduce the complexity of full parsing, help analyze the general structure of complex sentences, and provide important clues for detecting main predicates in Chinese sentences. In this paper, we propose a 2-phase hybrid approach for MNP identification which adopts salient features such as expanded chunks and classified punctuations to improve performance. Experimental result shows a high quality performance of 89.66% in $F_1$-measure.
Keywords
Maximal-Length Noun Phrase(MNP); Expanded Chunk; Classified Punctuation;
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