CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
Event Detection via Gated Multilingual Attention Mechanism
Jian Liu; Chen, Yubo; Liu, Kang; Zhao, Jun
Conference NameAmerican Association for AI National Conference(AAAI 2018)
Conference Date2018.02.02-2018.02.07
Conference PlaceNew Orleans, USA.

Identifying event instance in text plays a critical role in building

NLP applications such as Information Extraction (IE)

system. However, most existing methods for this task focus

only on monolingual clues of a specific language and ignore

the massive information provided by other languages.

Data scarcity and monolingual ambiguity hinder the performance

of these monolingual approaches. In this paper, we

propose a novel multilingual approach — dubbed as Gated

MultiLingual Attention (GMLATT) framework — to address

the two issues simultaneously. In specific, to alleviate

data scarcity problem, we exploit the consistent information

in multilingual data via context attention mechanism.

Which takes advantage of the consistent evidence in multilingual

data other than learning only from monolingual data. To

deal with monolingual ambiguity problem, we propose gated

cross-lingual attention to exploit the complement information

conveyed by multilingual data, which is helpful for the disambiguation.

The cross-lingual attention gate serves as a sentinel

modelling the confidence of the clues provided by other

languages and controls the information integration of various

languages. We have conducted extensive experiments on

the ACE 2005 benchmark. Experimental results show that our

approach significantly outperforms state-of-the-art methods.

Indexed ByEI
Document Type会议论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jian Liu,Chen, Yubo,Liu, Kang,et al. Event Detection via Gated Multilingual Attention Mechanism[C],2018.
Files in This Item: Download All
File Name/Size DocType Version Access License
8.AAAI2018liujian.pd(718KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jian Liu]'s Articles
[Chen, Yubo]'s Articles
[Liu, Kang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jian Liu]'s Articles
[Chen, Yubo]'s Articles
[Liu, Kang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jian Liu]'s Articles
[Chen, Yubo]'s Articles
[Liu, Kang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 8.AAAI2018liujian.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.