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SemEval 2022 Task 2 Multilingual Idiomaticity Detection and Sentence Embedding https://sites.google.com/view/semeval2022task2-idiomaticity We are excited to announce the SemEval 2022 Task seeking to encourage the development of methods aimed at better identification and representation of Idiomatic Multiword Expressions (MWEs). Motivation ================================================ By and large, the use of compositionality of word representations has been successful in capturing the meaning of sentences. However, there is an important set of phrases - those which are idiomatic - which are inherently not compositional. Early attempts to represent idiomatic phrases in non-contextual embeddings involved the extraction of frequently occurring n-grams from text (such as “big fish”) before learning representations of the phrase based on their context. However, the effectiveness of this method drops off significantly as the length of the idiomatic phrase increases as a result of data sparsity. More recent studies show that even state-of-the-art pre-trained contextual models (e.g. BERT) cannot accurately represent idiomatic expressions. Task Overview ================================================ Given this shortcoming in existing state-of-the-art models, this task (part of SemEval 2022) is aimed at detecting and representing multiword expressions (MWEs) which are potentially idiomatic phrases across English, Portuguese and Galician in both zero shot and one-shot shot settings. Participants have the freedom to choose a subset of subtasks or variations (settings) that they'd like to participate in. You can NOT pick a subset of languages. This task consists of two subtasks: *Subtask A * ------------------------------------------------ A binary classification task aimed at determining whether a sentence contains an idiomatic expression. *Subtask B * ------------------------------------------------ The task of generating a sentence embedding that represents the correct meaning of the sentence, be it idiomatic or literal, as measured by semantic text similarity between sentences. Important Dates ================================================ Training data available: September 3, 2021 [NOW AVAILABLE] Evaluation start: January 10, 2022 Evaluation end: (TBC) January 31, 2022 Paper submissions due: (TBC) February 23, 2022 Notification to authors: March 31, 2022 Organisation ================================================ Harish Tayyar Madabushi, University of Sheffield, UK. Edward Gow-Smith, University of Sheffield, UK. Marcos Garcia, Universidade de Santiago de Compostela, Spain Carolina Scarton, University of Sheffield, UK. Marco Idiart, Federal University of Rio Grande do Sul, Brazil. Aline Villavicencio, University of Sheffield, UK. For more information, see: https://sites.google.com/view/semeval2022task2-idiomaticity Best wishes, Harish -- *Carolina Scarton* Academic Fellow Department of Computer Science University of Sheffield http://staffwww.dcs.shef.ac.uk/people/C.Scarton/
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