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AdMIRe: Advancing Multimodal Idiomaticity Representation (SemEval-2025 Task 1) - Labelled Datasets

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DataCite Commons2026-02-25 更新2026-05-04 收录
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https://orda.shef.ac.uk/articles/dataset/AdMIRe_Advancing_Multimodal_Idiomaticity_Representation_SemEval-2025_Task_1_-_Labelled_Datasets/28436600/2
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资源简介:
The <b>AdMIRe </b>shared task was organised and run as SemEval-2025 Task 1: https://semeval.github.io/SemEval2025/<br>The datasets contain potentially idiomatic expressions (PIEs) in English (EN) and Brazilian Portuguese (PT), context sentences in which the expressions are used in either a literal or idiomatic sense and associated images depicting the expressions with either a single image or a sequence of three images capturing change over time (like a comic strip).<br>See the task website (https://semeval2025-task1.github.io/), the attached task description document (SemEval_2025_Task_1__ADMIRE___Advancing_Multimodal_Idiomaticity_Representation.pdf) or the following task paper for more information:Thomas Pickard, Aline Villavicencio, Maggie Mi, Wei He, Dylan Phelps, Carolina Scarton and Marco Idiart. 2025. <b>SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity Representation.</b> <i>Proceedings of the 19th International Workshop on Semantic Evaluations (SemEval-2025). Association for Computational Linguistics, Vienna, Austria.</i>
提供机构:
The University of Sheffield
创建时间:
2025-08-13
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