The first edition of Entity-Aware Machine Translation (EA-MT) is a new shared task whose goal is to track progress and encourage the development of MT systems that can better handle the translation of text containing entities whose names differ significantly across languages. Given a sentence s in English containing an entity e, the task is to translate s into a target language while adapting the name of e to the target language in order to preserve the original meaning of the sentence.
Publicación
Simone Conia, Min Li, Roberto Navigli, and Saloni Potdar. 2025. SemEval-2025 Task 2: Entity-Aware Machine Translation. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 2535–2557, Vienna, Austria. Association for Computational Linguistics.
Idioma
Español
Inglés
Árabe
Alemán
Francés
Italiano
Coreano
Chino
URL Tarea
NLP topic
Dataset
Año
2025
Enlace publicación
Métrica Ranking
Comet

