S-NLP at SemEval-2021 Task 5: An Analysis of Dual Networks for Sequence Tagging
Viet Anh Nguyen, Tam Minh Nguyen, Huy Quang Dao, Quang Huu Pham
Abstract
The SemEval 2021 task 5: Toxic Spans Detection is a task of identifying considered-toxic spans in text, which provides a valuable, automatic tool for moderating online contents. This paper represents the second-place method for the task, an ensemble of two approaches. While one approach relies on combining different embedding methods to extract diverse semantic and syntactic representations of words in context; the other utilizes extra data with a slightly customized Self-training, a semi-supervised learning technique, for sequence tagging problems. Both of our architectures take advantage of a strong language model, which was fine-tuned on a toxic classification task. Although experimental evidence indicates higher effectiveness of the first approach than the second one, combining them leads to our best results of 70.77 F1-score on the test dataset.- Anthology ID:
- 2021.semeval-1.120
- Volume:
- Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 888–897
- Language:
- URL:
- https://aclanthology.org/2021.semeval-1.120
- DOI:
- 10.18653/v1/2021.semeval-1.120
- Cite (ACL):
- Viet Anh Nguyen, Tam Minh Nguyen, Huy Quang Dao, and Quang Huu Pham. 2021. S-NLP at SemEval-2021 Task 5: An Analysis of Dual Networks for Sequence Tagging. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 888–897, Online. Association for Computational Linguistics.
- Cite (Informal):
- S-NLP at SemEval-2021 Task 5: An Analysis of Dual Networks for Sequence Tagging (Nguyen et al., SemEval 2021)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2021.semeval-1.120.pdf