2025 SEMEVAL SemEval 2025

AlexUNLP-NB at SemEval-2025 Task 1: A Pipeline for Idiom Disambiguation and Visual Representation

Abstract

AbstractThis paper describes our system developed for SemEval-2025 Task 1, subtask A. This sharedsubtask focuses on multilingual idiom recognition and the ranking of images based on howwell they represent the sense in which a nominal compound is used within a given contextual sentence. This study explores the use of a pipeline, where task-specific models are sequentially employed to address each problem step by step. The process involves three key steps: first, identifying whether idioms are in their literal or figurative form; second, transforming them if necessary; and finally, usingthe final form to rank the input images.

🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — literal figurative
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio