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	A Convolution BiLSTM Neural Network Model for Chinese Event Extraction
	Zeng, Ying ; Yang, Honghui ; Feng, Yansong ; Wang, Zheng ; Zhao, Dongyan
	2016
关键词	Event extraction Neural network Chinese language processing
英文摘要	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.; National High Technology R&D Program of China [2015AA015403, 2014AA015102]; Natural Science Foundation of China [61202233, 61272344, 61370055]; IBM Research; CPCI-S(ISTP); 275-287; 10102
语种	英语
出处	5th International Conference on Natural Language Processing and Chinese Computing (NLPCC) / 24th International Conference on Computer Processing of Oriental Languages (ICCPOL)
DOI标识	10.1007/978-3-319-50496-4_23
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470114]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zeng, Ying,Yang, Honghui,Feng, Yansong,et al. A Convolution BiLSTM Neural Network Model for Chinese Event Extraction. 2016-01-01.

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