High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts

Hamza Alami, Abdessamad Benlahbib, Ahmed Alami


Abstract
This paper presents our proposed methods for the iSarcasmEval shared task. The shared task consists of three different subtasks. We participate in both subtask A and subtask C. The purpose of subtask A was to predict if a text is sarcastic while the aim of subtask C is to determine which text is sarcastic given a sarcastic text and its non-sarcastic rephrase. Both of the developed solutions used BERT pre-trained models. The proposed models are optimized on simple objectives and are easy to grasp. However, despite their simplicity, our methods ranked 4 and 2 in iSarcasmEval subtask A and subtask C for Arabic texts.
Anthology ID:
2022.semeval-1.116
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:
840–843
Language:
URL:
https://aclanthology.org/2022.semeval-1.116
DOI:
10.18653/v1/2022.semeval-1.116
Bibkey:
Cite (ACL):
Hamza Alami, Abdessamad Benlahbib, and Ahmed Alami. 2022. High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 840–843, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts (Alami et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.116.pdf
Data
iSarcasmEval