2020
AAAI
AAAI 2020
One Homonym per Translation
Abstract
Abstract The study of homonymy is vital to resolving fundamental problems in lexical semantics. In this paper, we propose four hypotheses that characterize the unique behavior of homonyms in the context of translations, discourses, collocations, and sense clusters. We present a new annotated homonym resource that allows us to test our hypotheses on existing WSD resources. The results of the experiments provide strong empirical evidence for the hypotheses. This study represents a step towards a computational method for distinguishing between homonymy and polysemy, and constructing a definitive inventory of coarse-grained senses.
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Interdisciplinary Bridge
— Artificial Intelligence and Interdisciplinary and Natural Language Processing
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Keyword Pioneer
— homonymy detection
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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
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Resources & Methods > Lexical Semantics
Interdisciplinary > Linguistics
Interdisciplinary > Linguistics > Semantics
Natural Language Processing > Understanding > Lexical Semantics
Artificial Intelligence > Core AI > Knowledge