Thanks :) 1) I think learning entity embeddings using the Doc2Vec (paragraph vector) model is an interesting idea, but we did not test it. 2) This tool was initially developed to address the entity linking task. Mapping words and entities into a same vector space enables to model the contextual information that is useful for entity linking. For details, please refer to this paper: Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation: https://arxiv.org/pdf/1601.01343.pdf