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arXiv 2204.10050cs.CL

SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding

University of Sheffield(谢菲尔德大学);Universidade de Santiago de Compostela(圣地亚哥德孔波斯特拉大学);Federal University of Rio Grande do Sul(南里奥格兰德联邦大学)

Harish Tayyar Madabushi, Edward Gow-Smith, Marcos Garcia, Carolina Scarton, Marco Idiart, Aline Villavicencio

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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