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.
REF build a neural-network post-processing system called AutoExtend that takes word embeddings and learns embeddings for synsets and lexemes.
AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes
ArXiv
ArXiv
Computer Science