Papers with k-NN

2 papers
Zuo Zhuan Ancient Chinese Dataset for Word Sense Disambiguation (2022.naacl-srw)

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Challenge: Word Sense Disambiguation (WSD) is a core task in natural language processing . ancient Chinese has rarely been used in WSD tasks due to lack of a dataset .
Approach: They annotate ancient Chinese text Zuo Zhuan using a copyright-free dictionary . they apply a method to find the most appropriate sense in a context using k-NN .
Outcome: The proposed dataset will be available on GitHub.
Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation (P19-1)

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Challenge: Contextual embeddings address the problem of meaning conflation hampering word embeddables.
Approach: They propose a method that creates sense-level embeddings with full-coverage of WordNet without recourse to explicit sense distributions or task-specific modelling.
Outcome: The proposed method surpasses previous systems using powerful models and is robust when ignoring part-of-speech and lemma features.

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