Sentence-Level Resampling for Named Entity Recognition

Xiaochen Wang, Yue Wang


Abstract
As a fundamental task in natural language processing, named entity recognition (NER) aims to locate and classify named entities in unstructured text. However, named entities are always the minority among all tokens in the text. This data imbalance problem presents a challenge to machine learning models as their learning objective is usually dominated by the majority of non-entity tokens. To alleviate data imbalance, we propose a set of sentence-level resampling methods where the importance of each training sentence is computed based on its tokens and entities. We study the generalizability of these resampling methods on a wide variety of NER models (CRF, Bi-LSTM, and BERT) across corpora from diverse domains (general, social, and medical texts). Extensive experiments show that the proposed methods improve span-level macro F1-scores of the evaluated NER models on multiple corpora, frequently outperforming sub-sentence-level resampling, data augmentation, and special loss functions such as focal and Dice loss.
Anthology ID:
2022.naacl-main.156
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2151–2165
Language:
URL:
https://aclanthology.org/2022.naacl-main.156
DOI:
10.18653/v1/2022.naacl-main.156
Bibkey:
Cite (ACL):
Xiaochen Wang and Yue Wang. 2022. Sentence-Level Resampling for Named Entity Recognition. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2151–2165, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
Sentence-Level Resampling for Named Entity Recognition (Wang & Wang, NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-main.156.pdf
Code
 xiaochen-w/ner_adaptive_resampling