Contextual embeddings are propagated through WordNet to produce full-coverage sense representations that let a simple k-NN classifier outperform prior neural WSD models.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CL 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
An adapted WSD system with contextual and sense embeddings places second in the WiC challenge while avoiding task-specific training data.
citing papers explorer
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Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation
Contextual embeddings are propagated through WordNet to produce full-coverage sense representations that let a simple k-NN classifier outperform prior neural WSD models.
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LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)
An adapted WSD system with contextual and sense embeddings places second in the WiC challenge while avoiding task-specific training data.