A Machine-Learning Approach to Estimating the Referential Properties of Japanese Noun Phrases

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dc.creatorMurata, Masaki
dc.creatorUchimoto, Kiyotaka
dc.creatorMa, Qing
dc.creatorIsahara, Hitoshi
dc.date2001-03-12
dc.date.accessioned2026-07-07T03:17:00Z
dc.date.available2026-07-07T03:17:00Z
dc.descriptionThe referential properties of noun phrases in the Japanese language, which has no articles, are useful for article generation in Japanese-English machine translation and for anaphora resolution in Japanese noun phrases. They are generally classified as generic noun phrases, definite noun phrases, and indefinite noun phrases. In the previous work, referential properties were estimated by developing rules that used clue words. If two or more rules were in conflict with each other, the category having the maximum total score given by the rules was selected as the desired category. The score given by each rule was established by hand, so the manpower cost was high. In this work, we automatically adjusted these scores by using a machine-learning method and succeeded in reducing the amount of manpower needed to adjust these scores.
dc.description9 pages. Computation and Language. This paper is included in the book entitled by "Computational Linguistics and Intelligent Text Processing, Second International Conference, CICLing 2001, Mexico City, February 2001 Proceedings", Alexander Gelbukh (Ed.), Springer Publisher, ISSN 0302-9743, ISBN 3-540-41687-0
dc.identifierhttps://arxiv.org/abs/cs/0103011
dc.identifierhttp://arxiv.org/abs/cs/0103011
dc.identifierCICLing'2001, Mexico City, February 2001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30567
dc.subjectComputation and Language
dc.subjectH.3.3; I.2.7
dc.titleA Machine-Learning Approach to Estimating the Referential Properties of Japanese Noun Phrases
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