What I meant is that Word2Vec and Glove have only one feature vector that for the string “play” that encapsulates all it’s word senses, where as contextual embedding systems such as BERT and ELMO generate will generate different vector for the string “play” given it’s context.

<Microsoft Open Source Engineer> I am an AI enthusiast with a passion for engaging with new technologies, history, and computational medicine.

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