2022
ACL
ACL 2022
BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection
Abstract
AbstractWe propose a solution for the LSCDiscovery shared task on Lexical Semantic Change Detection in Spanish. Our approach is based on generating lexical substitutes that describe old and new senses of a given word. This approach achieves the second best result in sense loss and sense gain detection subtasks. By observing those substitutes that are specific for only one time period, one can understand which senses were obtained or lost. This allows providing more detailed information about semantic change to the user and makes our method interpretable.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Keyword Pioneer
— sense loss
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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, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Interpretability
Machine Learning > Core Methods > Classification
Machine Learning > Learning Types > Unsupervised Learning
Natural Language Processing > Resources & Methods > Lexical Semantics
Machine Learning > Learning Types > Representation Learning
Artificial Intelligence > Core AI > Natural Language Processing