Abstract
This paper presents an empirical work for Vietnamese NP chunking task. We show how to build an annotation corpus of NP chunking and how discriminative sequence models are trained using the corpus. Experiment results using 5 fold cross validation test show that discriminative sequence learning are well suitable for Vietnamese chunking. In addition, by empirical experiments we show that the part of speech information contribute significantly to the performance of there learning models.
Cite
CITATION STYLE
Nguyen, L. M., Nguyen, H. T., Nguyen, P. T., Ho, T. B., & Shimazu, A. (2009). An Empirical Study of Vietnamese Noun Phrase Chunking with Discriminative Sequence Models. In Proceedings of the 7th Workshop on Asian Language Resources, ALR 2009 - in conjunction with the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (pp. 9–16). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1690299.1690301
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