2025
SEMEVAL
SemEval 2025
WC Team at SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification leveraging monolingual and multilingual BERT models
Abstract
AbstractThis paper presents our system developed for SemEval-2025 Task 6: PromiseEval: Multinational, Multilingual, Multi-Industry Promise Verification. The task aims at identifying “promises” made and “evidence” provided in company ESG statements for various languages. Our team participated in Subtasks 1 and 2 for the languages English, French, and Japanese. In this work, we propose using BERT and finetuning it to better address the task. We achieve competitive results, especially for English and Japanese.
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Interdisciplinary Bridge
— Deep Learning and Natural Language Processing
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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