We present 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.
The AutoExtend REF approach can be used to learn embeddings for lexemes and synsets of a lexical resource.
AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes
ArXiv
ArXiv
Computer Science