Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
Meihan Tong, Shuai Wang, Bin Xu, Yixin Cao, Minghui Liu, Lei Hou, Juanzi Li
Abstract
Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to iden- tify and classify named entity mentions. Pro- totypical network shows superior performance on few-shot NER. However, existing prototyp- ical methods fail to differentiate rich seman- tics in other-class words, which will aggravate overfitting under few shot scenario. To address the issue, we propose a novel model, Mining Undefined Classes from Other-class (MUCO), that can automatically induce different unde- fined classes from the other class to improve few-shot NER. With these extra-labeled unde- fined classes, our method will improve the dis- criminative ability of NER classifier and en- hance the understanding of predefined classes with stand-by semantic knowledge. Experi- mental results demonstrate that our model out- performs five state-of-the-art models in both 1- shot and 5-shots settings on four NER bench- marks. We will release the code upon accep- tance. The source code is released on https: //github.com/shuaiwa16/OtherClassNER.git.- Anthology ID:
- 2021.acl-long.487
- Volume:
- Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
- Venues:
- ACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6236–6247
- Language:
- URL:
- https://preview.aclanthology.org/icon-24-ingestion/2021.acl-long.487/
- DOI:
- 10.18653/v1/2021.acl-long.487
- Cite (ACL):
- Meihan Tong, Shuai Wang, Bin Xu, Yixin Cao, Minghui Liu, Lei Hou, and Juanzi Li. 2021. Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 6236–6247, Online. Association for Computational Linguistics.
- Cite (Informal):
- Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition (Tong et al., ACL-IJCNLP 2021)
- PDF:
- https://preview.aclanthology.org/icon-24-ingestion/2021.acl-long.487.pdf
- Code
- shuaiwa16/OtherClassNER
- Data
- CLUENER2020