CNNBiF: CNN-based Bigram Features for Named Entity Recognition
Chul Sung, Vaibhava Goel, Etienne Marcheret, Steven Rennie, David Nahamoo
Abstract
Transformer models fine-tuned with a sequence labeling objective have become the dominant choice for named entity recognition tasks. However, a self-attention mechanism with unconstrained length can fail to fully capture local dependencies, particularly when training data is limited. In this paper, we propose a novel joint training objective which better captures the semantics of words corresponding to the same entity. By augmenting the training objective with a group-consistency loss component we enhance our ability to capture local dependencies while still enjoying the advantages of the unconstrained self-attention mechanism. On the CoNLL2003 dataset, our method achieves a test F1 of 93.98 with a single transformer model. More importantly our fine-tuned CoNLL2003 model displays significant gains in generalization to out of domain datasets: on the OntoNotes subset we achieve an F1 of 72.67 which is 0.49 points absolute better than the baseline, and on the WNUT16 set an F1 of 68.22 which is a gain of 0.48 points. Furthermore, on the WNUT17 dataset we achieve an F1 of 55.85, yielding a 2.92 point absolute improvement.- Anthology ID:
- 2021.findings-emnlp.87
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2021
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- Findings
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1016–1021
- Language:
- URL:
- https://aclanthology.org/2021.findings-emnlp.87
- DOI:
- 10.18653/v1/2021.findings-emnlp.87
- Cite (ACL):
- Chul Sung, Vaibhava Goel, Etienne Marcheret, Steven Rennie, and David Nahamoo. 2021. CNNBiF: CNN-based Bigram Features for Named Entity Recognition. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 1016–1021, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- CNNBiF: CNN-based Bigram Features for Named Entity Recognition (Sung et al., Findings 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.findings-emnlp.87.pdf
- Data
- CoNLL 2003