Retrofitting Sense-Specific Word Vectors Using Parallel Text
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Word AlignmentWord Sense DisambiguationSimilar Papers 제목 키워드 기반
Coming to its senses: Lessons learned from Approximating Retrofitted BERT representations for Word Sense information
Retrofitting static vector space word representations using external knowledge bases has yielded substantial improvements in their lexical-semantic capacities but is non-trivial to apply to contextual word embeddings (CW…
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Semantic specialization of distributional word vectors, referred to as retrofitting, is a process of fine-tuning word vectors using external lexical knowledge in order to better embed some semantic relation. Existing ret…
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Word Embeddings are able to capture lexico-semantic information but remain flawed in their inability to assign unique representations to different senses of a polysemous words. They also fail to include information from …
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Distributional Semantics Models(DSM) derive word space from linguistic items in context. Meaning is obtained by defining a distance measure between vectors corresponding to lexical entities. Such vectors present several …
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Retrofitting techniques, which inject external resources into word representations, have compensated the weakness of distributed representations in semantic and relational knowledge between words. Implicitly retrofitting…
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