Abstract
Chineseword segmentation and POS tagging are arguably the most fundamental tasks in Chinese natural language processing. In this paper, we show an ensemble approach for segmentation and POS tagging, combining both discriminative and generative methods to get the advantage of both worlds. Our approach achieved the F1-score of 96.65% and 91.55% for segmentation and tagging respectively in the contest ofNLPCC 2015 Shared Task 1, obtained the 1st place for both tasks.
Cite
CITATION STYLE
Min, K., Ma, C., Zhao, T., & Li, H. (2015). BosonNLP: An ensemble approach for word segmentation and POS tagging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9362, pp. 520–526). Springer Verlag. https://doi.org/10.1007/978-3-319-25207-0_48
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