Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training

Yun Hu, Yeshuang Zhu, Jinchao Zhang, Changwen Zheng, Jie Zhou


Anthology ID:
2021.findings-acl.143
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1641–1652
Language:
URL:
https://aclanthology.org/2021.findings-acl.143
DOI:
10.18653/v1/2021.findings-acl.143
Bibkey:
Cite (ACL):
Yun Hu, Yeshuang Zhu, Jinchao Zhang, Changwen Zheng, and Jie Zhou. 2021. Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1641–1652, Online. Association for Computational Linguistics.
Cite (Informal):
Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training (Hu et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.143.pdf
Data
Weibo NER