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    <abstract>We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied with novel vector representations of Chinese characters that capture rich contextual information and lower-than-character level features. The proposed model is extensively evaluated and compared with a state-of-the-art tagger respectively on CTB5, CTB9 and UD Chinese. The experimental results indicate that our model is accurate and robust across datasets in different sizes, genres and annotation schemes. We obtain state-of-the-art performance on CTB5, achieving 94.38 F1-score for joint segmentation and POS tagging.</abstract>
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%0 Conference Proceedings
%T Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF
%A Shao, Yan
%A Hardmeier, Christian
%A Tiedemann, Jörg
%A Nivre, Joakim
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F shao-etal-2017-character
%X We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied with novel vector representations of Chinese characters that capture rich contextual information and lower-than-character level features. The proposed model is extensively evaluated and compared with a state-of-the-art tagger respectively on CTB5, CTB9 and UD Chinese. The experimental results indicate that our model is accurate and robust across datasets in different sizes, genres and annotation schemes. We obtain state-of-the-art performance on CTB5, achieving 94.38 F1-score for joint segmentation and POS tagging.
%U https://aclanthology.org/I17-1018
%P 173-183

Markdown (Informal)

[Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF](https://aclanthology.org/I17-1018) (Shao et al., IJCNLP 2017)

• Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF (Shao et al., IJCNLP 2017)

ACL

• Yan Shao, Christian Hardmeier, Jörg Tiedemann, and Joakim Nivre. 2017. Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 173–183, Taipei, Taiwan. Asian Federation of Natural Language Processing.