AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes

July 04, 2015 Β· Declared Dead Β· πŸ› Annual Meeting of the Association for Computational Linguistics

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Authors Sascha Rothe, Hinrich SchΓΌtze arXiv ID 1507.01127 Category cs.CL: Computation & Language Citations 290 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 3 months ago
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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