| Resumen |
We present our systems and findings for the iSarcasmEval: Intended Sarcasm Detection In English and Arabic at SEMEVAL 2022. Specifically we take part in the Subtask A for the English language. The task aims to determine whether a text from social media (a tweet) is sarcastic or not. We model the problem using knowledge sources, a pre-trained language model on sentiment/emotion data and a dataset focused on intended sarcasm. Our submission ranked third place among 43 teams. In addition, we show a brief error analysis of our best model to investigate challenging examples for detecting sarcasm. © 2022 Association for Computational Linguistics. |
