DoSEA: A Domain-specific Entity-aware Framework for Cross-Domain Named Entity Recogition

Minghao Tang, Peng Zhang, Yongquan He, Yongxiu Xu, Chengpeng Chao, Hongbo Xu


Abstract
Cross-domain named entity recognition aims to improve performance in a target domain with shared knowledge from a well-studied source domain. The previous sequence-labeling based method focuses on promoting model parameter sharing among domains. However, such a paradigm essentially ignores the domain-specific information and suffers from entity type conflicts. To address these issues, we propose a novel machine reading comprehension based framework, named DoSEA, which can identify domain-specific semantic differences and mitigate the subtype conflicts between domains. Concretely, we introduce an entity existence discrimination task and an entity-aware training setting, to recognize inconsistent entity annotations in the source domain and bring additional reference to better share information across domains. Experiments on six datasets prove the effectiveness of our DoSEA. Our source code can be obtained from https://github.com/mhtang1995/DoSEA.
Anthology ID:
2022.coling-1.188
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
2147–2156
Language:
URL:
https://aclanthology.org/2022.coling-1.188
DOI:
Bibkey:
Cite (ACL):
Minghao Tang, Peng Zhang, Yongquan He, Yongxiu Xu, Chengpeng Chao, and Hongbo Xu. 2022. DoSEA: A Domain-specific Entity-aware Framework for Cross-Domain Named Entity Recogition. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2147–2156, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
DoSEA: A Domain-specific Entity-aware Framework for Cross-Domain Named Entity Recogition (Tang et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.188.pdf
Code
 mhtang1995/dosea
Data
CrossNER