UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations

Thanet Markchom, Huizhi Liang, Jiaoyan Chen


Abstract
In human languages, there are many presuppositional constructions that impose a constrain on the taxonomic relations between two nouns depending on their order. These constructions create a challenge in validating taxonomic relations in real-world contexts. In SemEval2022-Task3 Presupposed Taxonomies: Evaluating Neural Network Semantics (PreTENS), the organizers introduced a task regarding validating the taxonomic relations within a variety of presuppositional constructions. This task is divided into two subtasks: classification and regression. Each subtask contains three datasets in multiple languages, i.e., English, Italian and French. To tackle this task, this work proposes to fine-tune different BERT-based models pre-trained on different languages. According to the experimental results, the fine-tuned BERT-based models are effective compared to the baselines in classification. For regression, the fine-tuned models show promising performance with the possibility of improvement.
Anthology ID:
2022.semeval-1.33
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
260–265
Language:
URL:
https://aclanthology.org/2022.semeval-1.33
DOI:
10.18653/v1/2022.semeval-1.33
Bibkey:
Cite (ACL):
Thanet Markchom, Huizhi Liang, and Jiaoyan Chen. 2022. UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 260–265, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations (Markchom et al., SemEval 2022)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2022.semeval-1.33.pdf