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%0 Conference Proceedings
%T Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training
%A Hu, Yun
%A Zhu, Yeshuang
%A Zhang, Jinchao
%A Zheng, Changwen
%A Zhou, Jie
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F hu-etal-2021-toward
%R 10.18653/v1/2021.findings-acl.143
%U https://aclanthology.org/2021.findings-acl.143
%U https://doi.org/10.18653/v1/2021.findings-acl.143
%P 1641-1652

Markdown (Informal)

[Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training](https://aclanthology.org/2021.findings-acl.143) (Hu et al., Findings 2021)

• Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training (Hu et al., Findings 2021)

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.