Multi-sense embeddings through a word sense disambiguation process.

•Unsupervised word sense disambiguation technique for diverse NLP tasks.•Word embeddings combining sense disambiguation, improving its vector representation.•Synset embedding models can help to leverage the disambiguation of polysemous words.•Multi-sense embedding models provide better representation than single-sense ones.•Recurrent synset-embedding models can improve the quality of word representations.