AdMIRe: Advancing Multimodal Idiomaticity Representation (SemEval-2025 Task 1) - Labelled Datasets
The AdMIRe shared task was organised and run as SemEval-2025 Task 1: https://semeval.github.io/SemEval2025/
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).
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. SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity Representation. Proceedings of the 19th International Workshop on Semantic Evaluations (SemEval-2025). Association for Computational Linguistics, Vienna, Austria.
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