2025
ACL
ACL 2025
Spatial relation marking across languages: extraction, evaluation, analysis
Abstract
AbstractThis paper presents a novel task, detecting Spatial Relation Markers (SRMs, like English _**in** the bag_), across languages, alongside a model for this task, RUIMTE. Using a massively parallel corpus of Bible translations, the model is evaluated against existing and baseline models on the basis of a novel evaluation set. The model presents high quality SRM extraction, and an accurate identification of situations where language have zero-marked SRMs.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— spatial relation marker
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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