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 F1-measure.
The detailed explanation of Expanded Chunks and Classified Punctuations will be shown in Section 3.
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Bai, XM., Li, JJ., Kim, DI., Lee, JH. (2006). Identification of Maximal-Length Noun Phrases Based on Expanded Chunks and Classified Punctuations in Chinese. In: Matsumoto, Y., Sproat, R.W., Wong, KF., Zhang, M. (eds) Computer Processing of Oriental Languages. Beyond the Orient: The Research Challenges Ahead. ICCPOL 2006. Lecture Notes in Computer Science(), vol 4285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11940098_28
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DOI: https://doi.org/10.1007/11940098_28
Publisher Name: Springer, Berlin, Heidelberg
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