I suggest Gensim for Word2Vec.<p>Spacy is really fast, the author is extremely knowledgeable, and it works well on the datasets it was trained on. Problem with SpaCy for me was that it was pre-trained on those texts and it was not possible to train it on new things. Also their parser wasn&#x27;t very customizable.<p>This pre-trained model is borderline useless if you want to obtain good results on your data, which is probably very different from the data they trained on.<p>For NER in the Python world, the best option is pycrfsuite. It works really quickly and lets you easily define your own features.  CRFSuite itself is a work of art.  I only wish Okazaki incorporated 2nd order transitions because that makes a huge difference on some datasets.<p>CoreNLP is a lot worse than pyCRFsuite in terms of ease of integration and performance in my experience.  Particularly, if you want to define your own features.