  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.
