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A convolution BiLSTM neural network model for Chinese event extraction

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A convolution BiLSTM neural network model for Chinese event extraction. / Zeng, Ying; Yang, Honghui; Feng, Yansong et al.

Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings. ed. / Chin-Yew Lin; Nianwen Xue; Dongyan Zhao; Xuanjing Huang; Yansong Feng. Cham : Springer, 2016. p. 275-287 ( Lecture Notes in Computer Science; Vol. 10102).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Zeng, Y, Yang, H, Feng, Y, Wang, Z & Zhao, D 2016, A convolution BiLSTM neural network model for Chinese event extraction. in C-Y Lin, N Xue, D Zhao, X Huang & Y Feng (eds), Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings. Lecture Notes in Computer Science, vol. 10102, Springer, Cham, pp. 275-287. https://doi.org/10.1007/978-3-319-50496-4_23

APA

Zeng, Y., Yang, H., Feng, Y., Wang, Z., & Zhao, D. (2016). A convolution BiLSTM neural network model for Chinese event extraction. In C-Y. Lin, N. Xue, D. Zhao, X. Huang, & Y. Feng (Eds.), Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings (pp. 275-287). ( Lecture Notes in Computer Science; Vol. 10102). Springer. https://doi.org/10.1007/978-3-319-50496-4_23

Vancouver

Zeng Y, Yang H, Feng Y, Wang Z, Zhao D. A convolution BiLSTM neural network model for Chinese event extraction. In Lin C-Y, Xue N, Zhao D, Huang X, Feng Y, editors, Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings. Cham: Springer. 2016. p. 275-287. ( Lecture Notes in Computer Science). doi: 10.1007/978-3-319-50496-4_23

Author

Zeng, Ying ; Yang, Honghui ; Feng, Yansong et al. / A convolution BiLSTM neural network model for Chinese event extraction. Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings. editor / Chin-Yew Lin ; Nianwen Xue ; Dongyan Zhao ; Xuanjing Huang ; Yansong Feng. Cham : Springer, 2016. pp. 275-287 ( Lecture Notes in Computer Science).

Bibtex

@inproceedings{c81691085940412c9d301ae24fc93e6a,
title = "A convolution BiLSTM neural network model for Chinese event extraction",
abstract = "Chinese event extraction is a challenging task in information extraction. Previous approaches highly depend on sophisticated feature engineering and complicated natural language processing (NLP) tools. In this paper, we first come up with the language specific issue in Chinese event extraction, and then propose a convolution bidirectional LSTM neural network that combines LSTM and CNN to capture both sentence-level and lexical information without any hand-craft features. Experiments on ACE 2005 dataset show that our approaches can achieve competitive performances in both trigger labeling and argument role labeling.",
author = "Ying Zeng and Honghui Yang and Yansong Feng and Zheng Wang and Dongyan Zhao",
note = "The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-50496-4_23",
year = "2016",
month = dec,
day = "2",
doi = "10.1007/978-3-319-50496-4_23",
language = "English",
isbn = "9783319504957 ",
series = " Lecture Notes in Computer Science",
publisher = "Springer",
pages = "275--287",
editor = "Chin-Yew Lin and Nianwen Xue and Dongyan Zhao and Xuanjing Huang and Yansong Feng",
booktitle = "Natural Language Understanding and Intelligent Applications",

}

RIS

TY - GEN

T1 - A convolution BiLSTM neural network model for Chinese event extraction

AU - Zeng, Ying

AU - Yang, Honghui

AU - Feng, Yansong

AU - Wang, Zheng

AU - Zhao, Dongyan

N1 - The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-50496-4_23

PY - 2016/12/2

Y1 - 2016/12/2

N2 - Chinese event extraction is a challenging task in information extraction. Previous approaches highly depend on sophisticated feature engineering and complicated natural language processing (NLP) tools. In this paper, we first come up with the language specific issue in Chinese event extraction, and then propose a convolution bidirectional LSTM neural network that combines LSTM and CNN to capture both sentence-level and lexical information without any hand-craft features. Experiments on ACE 2005 dataset show that our approaches can achieve competitive performances in both trigger labeling and argument role labeling.

AB - Chinese event extraction is a challenging task in information extraction. Previous approaches highly depend on sophisticated feature engineering and complicated natural language processing (NLP) tools. In this paper, we first come up with the language specific issue in Chinese event extraction, and then propose a convolution bidirectional LSTM neural network that combines LSTM and CNN to capture both sentence-level and lexical information without any hand-craft features. Experiments on ACE 2005 dataset show that our approaches can achieve competitive performances in both trigger labeling and argument role labeling.

U2 - 10.1007/978-3-319-50496-4_23

DO - 10.1007/978-3-319-50496-4_23

M3 - Conference contribution/Paper

SN - 9783319504957

T3 - Lecture Notes in Computer Science

SP - 275

EP - 287

BT - Natural Language Understanding and Intelligent Applications

A2 - Lin, Chin-Yew

A2 - Xue, Nianwen

A2 - Zhao, Dongyan

A2 - Huang, Xuanjing

A2 - Feng, Yansong

PB - Springer

CY - Cham

ER -