NLP@UIT at FigLang-EMNLP 2022: A Divide-and-Conquer System For Shared Task On Understanding Figurative Language

Khoa Thi-Kim Phan, Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen


Abstract
This paper describes our submissions to the EMNLP 2022 shared task on Understanding Figurative Language as part of the Figurative Language Workshop (FigLang 2022). Our systems based on pre-trained language model T5 are divide-and-conquer models which can address both two requirements of the task: 1) classification, and 2) generation. In this paper, we introduce different approaches in which each approach we employ a processing strategy on input model. We also emphasize the influence of the types of figurative language on our systems.
Anthology ID:
2022.flp-1.21
Volume:
Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Editors:
Debanjan Ghosh, Beata Beigman Klebanov, Smaranda Muresan, Anna Feldman, Soujanya Poria, Tuhin Chakrabarty
Venue:
Fig-Lang
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
150–153
Language:
URL:
https://aclanthology.org/2022.flp-1.21
DOI:
10.18653/v1/2022.flp-1.21
Bibkey:
Cite (ACL):
Khoa Thi-Kim Phan, Duc-Vu Nguyen, and Ngan Luu-Thuy Nguyen. 2022. NLP@UIT at FigLang-EMNLP 2022: A Divide-and-Conquer System For Shared Task On Understanding Figurative Language. In Proceedings of the 3rd Workshop on Figurative Language Processing (FLP), pages 150–153, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
NLP@UIT at FigLang-EMNLP 2022: A Divide-and-Conquer System For Shared Task On Understanding Figurative Language (Phan et al., Fig-Lang 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.flp-1.21.pdf