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Abstract. Words with multiple meanings are a phenomenon inherent to any natural language. In this work, we study the effects of such lexical ambiguities.
To our knowledge this is the first work that investigates the efficacy of word sense disambiguation for facilitating second language vocabulary learning.
Apr 21, 2023 · Word Sense Disambiguation (WSD) is a subtask of Natural Language Processing that deals with the problem of identifying the correct sense of a word in context.
Word Sense Disambiguation (WSD) is the proc- ess of distinguishing between different senses of a word. In general, the disambiguation rules dif-.
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To our knowledge this is the first work that investigates the efficacy of word sense disambiguation for facilitating second language vocabulary learning.
Semantic concordance: a corpus in which each open-‐class word is labeled with a sense from a specific dictionary/thesaurus. • SemCor: 234,000 words from Brown ...
Feb 19, 2015 · Word sense disambiguation is an open problem, so the success of any approach will depend a lot on your particular data.
Word sense disambiguation (WSD), identifying the most suitable meaning of ambiguous words in the given contexts according to a predefined sense inventory ...
Abstract. In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from ...
The problem: Improvement of English vocabulary by performing sense disambiguation for homonyms to help ESL students in vocabulary learning. Solution: Both ...