@inproceedings{huang-etal-2016-chinese-tense,
title = "{C}hinese Tense Labelling and Causal Analysis",
author = "Huang, Hen-Hsen and
Yang, Chang-Rui and
Chen, Hsin-Hsi",
editor = "Matsumoto, Yuji and
Prasad, Rashmi",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/C16-1210",
pages = "2227--2237",
abstract = "This paper explores the role of tense information in Chinese causal analysis. Both tasks of causal type classification and causal directionality identification are experimented to show the significant improvement gained from tense features. To automatically extract the tense features, a Chinese tense predictor is proposed. Based on large amount of parallel data, our semi-supervised approach improves the dependency-based convolutional neural network (DCNN) models for Chinese tense labelling and thus the causal analysis.",
}
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%0 Conference Proceedings
%T Chinese Tense Labelling and Causal Analysis
%A Huang, Hen-Hsen
%A Yang, Chang-Rui
%A Chen, Hsin-Hsi
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F huang-etal-2016-chinese-tense
%X This paper explores the role of tense information in Chinese causal analysis. Both tasks of causal type classification and causal directionality identification are experimented to show the significant improvement gained from tense features. To automatically extract the tense features, a Chinese tense predictor is proposed. Based on large amount of parallel data, our semi-supervised approach improves the dependency-based convolutional neural network (DCNN) models for Chinese tense labelling and thus the causal analysis.
%U https://aclanthology.org/C16-1210
%P 2227-2237
Markdown (Informal)
[Chinese Tense Labelling and Causal Analysis](https://aclanthology.org/C16-1210) (Huang et al., COLING 2016)
ACL
- Hen-Hsen Huang, Chang-Rui Yang, and Hsin-Hsi Chen. 2016. Chinese Tense Labelling and Causal Analysis. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2227–2237, Osaka, Japan. The COLING 2016 Organizing Committee.