CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data
Yang, Hang; Chen, Yubo; Liu, Kang; Zhao, Jun
2018
Conference NameAnnual Meeting of Association for Computational Linguistics (ACL 2018)
Conference DateJul 15, 2018 - Jul 20, 2018
Conference PlaceMelbourne, Australia
Abstract

We present an event extraction framework

to detect event mentions and extract events

from the document-level financial news.

Up to now, methods based on supervised

learning paradigm gain the highest perfor-

mance in public datasets (such as ACE

20051, KBP 20152). These methods heav-

ily depend on the manually labeled train-

ing data. However, in particular areas,

such as financial, medical and judicial do-

mains, there is no enough labeled data due

to the high cost of data labeling process.

Moreover, most of the current methods

focus on extracting events from one sen-

tence, but an event is usually expressed

by multiple sentences in one document.

To solve these problems, we propose a

Document-level Chinese Financial Event

Extraction (DCFEE) system which can au-

tomatically generate a large scaled labeled

data and extract events from the whole

document. Experimental results demon-

strate the effectiveness of it.

Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26132
Collection模式识别国家重点实验室_自然语言处理
Affiliation中国科学院自动化研究所
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Yang, Hang,Chen, Yubo,Liu, Kang,et al. DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data[C],2018.
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