A Two-Stage Bi-LSTM Model for Chinese Company Name Recognition

被引:1
|
作者
Zeng, Jing [1 ,2 ,3 ]
Che, Jin [2 ]
Xing, Chunxiao [1 ]
Zhang, Liang-Jie [2 ,3 ]
机构
[1] Tsinghua Univ, Res Inst Informat Technol, Beijing, Peoples R China
[2] Kingdee Int Software Grp Co Ltd, Kingdee Res, Shenzhen, Peoples R China
[3] Natl Engn Res Ctr Supporting Software Enterprise, Shenzhen, Peoples R China
关键词
Name entity recognition; CRF; LSTM; Information extraction;
D O I
10.1007/978-3-319-94361-9_1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Chinese company name is a special name entity of organization, which plays a critical role in multiple application scenarios. Traditional rule-based or statistic based approaches that can achieve effective recognition for a company name at restriction environment, which is tricky to tailor the demands of real application scenarios. In this paper, we propose a two-stage Bi-LSTM model to achieve the Chinese company name recognition. The first stage is to detect the candidate Chinese company name by Bi-LSTM-CRF Model, and then the second stage is to further identify the company name via Bi-LSTM. We conduct the comparison experiment on a labelled benchmark dataset, the proposed approach achieves the 98.8% precision, 83.7% recall rate and 90.62% F-measure. It significantly outperforms traditional rule-based and statistics based approaches.
引用
收藏
页码:3 / 15
页数:13
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