A Convolution BiLSTM Neural Network Model for Chinese Event Extraction

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.

关键词： event extraction neural network Chinese language processing

作者: Ying Zeng Honghui Yang Yansong Feng Zheng Wang Dongyan Zhao

作者单位: Institute of Computer Science and Technology,Peking University,P.R. China School of Computing and Communications,Lancaster University,UK

会议类型: 国际会议

会议名称: 第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)

会议地点: 昆明

会议语种:英文

页码: 1-12

在线出版日期: 2016-12-02（万方平台首次上网日期，不代表论文的发表时间）