@inproceedings{tayyar-madabushi-etal-2022-semeval,
title = "{S}em{E}val-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding",
author = "Tayyar Madabushi, Harish and
Gow-Smith, Edward and
Garcia, Marcos and
Scarton, Carolina and
Idiart, Marco and
Villavicencio, Aline",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.13",
doi = "10.18653/v1/2022.semeval-1.13",
pages = "107--121",
abstract = "This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification task aimed at identifying whether a sentence contains an idiomatic expression, and (b) a task based on semantic text similarity which requires the model to adequately represent potentially idiomatic expressions in context. Each subtask includes different settings regarding the amount of training data. Besides the task description, this paper introduces the datasets in English, Portuguese, and Galician and their annotation procedure, the evaluation metrics, and a summary of the participant systems and their results. The task had close to 100 registered participants organised into twenty five teams making over 650 and 150 submissions in the practice and evaluation phases respectively.",
}
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%0 Conference Proceedings
%T SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding
%A Tayyar Madabushi, Harish
%A Gow-Smith, Edward
%A Garcia, Marcos
%A Scarton, Carolina
%A Idiart, Marco
%A Villavicencio, Aline
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F tayyar-madabushi-etal-2022-semeval
%X This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification task aimed at identifying whether a sentence contains an idiomatic expression, and (b) a task based on semantic text similarity which requires the model to adequately represent potentially idiomatic expressions in context. Each subtask includes different settings regarding the amount of training data. Besides the task description, this paper introduces the datasets in English, Portuguese, and Galician and their annotation procedure, the evaluation metrics, and a summary of the participant systems and their results. The task had close to 100 registered participants organised into twenty five teams making over 650 and 150 submissions in the practice and evaluation phases respectively.
%R 10.18653/v1/2022.semeval-1.13
%U https://aclanthology.org/2022.semeval-1.13
%U https://doi.org/10.18653/v1/2022.semeval-1.13
%P 107-121
Markdown (Informal)
[SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding](https://aclanthology.org/2022.semeval-1.13) (Tayyar Madabushi et al., SemEval 2022)
ACL