Abstract
This paper proposes a method of prepositional phrase (PP) identification by incorporating PP classification knowledge. When PPs act as different syntactic constituents, they have different characteristics in terms of location and context. In this paper, PPs are classified based on the context in which they appear. We select features based on the category of PPs to train multiple machine learning models for PP identification, and recombine these identification results. In this way, we can make full use of the complementary advantage of multiple models.
This work is supported by Humanities and Social Sciences Foundation for the Youth Scholars of Ministry of Education of China (№-14YJC740126) and National Natural Science Foundation of China (№-61402299)
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© 2015 Springer International Publishing Switzerland
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Zhou, Q., Zhang, L., Ye, N., Cai, D. (2015). Incorporating Prepositional Phrase Classification Knowledge in Prepositional Phrase Identification. In: Lu, Q., Gao, H. (eds) Chinese Lexical Semantics. CLSW 2015. Lecture Notes in Computer Science(), vol 9332. Springer, Cham. https://doi.org/10.1007/978-3-319-27194-1_57
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DOI: https://doi.org/10.1007/978-3-319-27194-1_57
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