preprint Open access

AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes

  • arXiv (Cornell University)
  • Cornell University
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Abstract

We present \textit{AutoExtend}, a system to learn embeddings for synsets and lexemes. It is flexible in that it can take any word embeddings as input and does not need an additional training corpus. The synset/lexeme embeddings obtained live in the same vector space as the word embeddings. A sparse tensor formalization guarantees efficiency and parallelizability. We use WordNet as a lexical resource, but AutoExtend can be easily applied to other resources like Freebase. AutoExtend achieves state-of-the-art performance on word similarity and word sense disambiguation tasks.

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Publication details

DOI
10.3115/v1/p15-1173
OpenAlex
W2963606136
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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