In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not considered in previous statistical (machine learning based) parsing methods: information about dependency relations among the case elements of a verb, and information about co-occurrence relations between a verb and its case element. This information can be collected from the results of automatic dependency parsing of large-scale corpora. The results of an experiment in which our method was used to rerank the results obtained using an existing machine learning based parsing method showed that our method can improve the accuracy of the results obtained using the existing method. © 2006 Association for Computational Linguistics.
CITATION STYLE
Abekawa, T., & Okumura, M. (2006). Japanese dependency parsing using co-occurrence information and a combination of case elements. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Vol. 1, pp. 833–840). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220175.1220280
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