Doing so allows us to reflect upon theoretical questions regarding the structure of the mental lexicon, and also puts into perspective a number of assumptions underlying recently proposed distributional text-based models.
we focus on word-embedding models which have been proposed to learn aspects of word meaning in a manner similar to humans.