SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic

Autor: Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, Walid Magdy
Přispěvatelé: Emerson, Guy, Schluter, Natalie, Stanovsky, Gabriel, Kumar, Ritesh, Palmer, Alexis, Schneider, Nathan, Singh, Siddharth, Ratan, Shyam
Jazyk: angličtina
Rok vydání: 2022
Zdroj: Abu Farha, I, Oprea, S, Wilson, S & Magdy, W 2022, SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic . in G Emerson, N Schluter, G Stanovsky, R Kumar, A Palmer, N Schneider, S Singh & S Ratan (eds), Proceedings of The 16th International Workshop on Semantic Evaluation 2022 . Stroudsburg, PA, USA, pp. 802-814, The 16th International Workshop on Semantic Evaluation 2022, 14/07/22 . https://doi.org/10.18653/v1/2022.semeval-1.111
DOI: 10.18653/v1/2022.semeval-1.111
Popis: iSarcasmEval is the first shared task to target intended sarcasm detection: the data for this task was provided and labelled by the authors of the texts themselves. Such an approach minimises the downfalls of other methods to collect sarcasm data, which rely on distant supervision or third-party annotations. The shared task contains two languages, English and Arabic, and three subtasks: sarcasm detection, sarcasm category classification, and pairwise sarcasm identification given a sarcastic sentence and its non-sarcastic rephrase. The task received submissions from 60 different teams, with the sarcasm detection task being the most popular. Most of the participating teams utilised pre-trained language models. In this paper, we provide an overview of the task, data, and participating teams
Databáze: OpenAIRE
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