Do multi-sense word embeddings learn more senses?

Márton Makrai, Veronika Lipp

Abstract: We analyze whether different sense vectors of the same word form in multi-sense word embeddings correspond to different concepts. On the more technical side of embedding-based dictionary induction, we also test whether the orthogonality constraint and related vector preprocessing techniques help in reverse nearest neighbor search. Both questions receive a negative answer.