If you're doing NLP in Python, there's no reason to use CoreNLP's parser from the NLTK wrapper. Communicating with the Java process over the file system or a socket introduces a tonne of unnecessary complications, slow-downs, invites encoding problems, etc.

spaCy's native Cython dependency parser is both faster and more accurate than CoreNLP.

The NP chunks example from the post:

    >>> from spacy.en import English
    >>> nlp = English()
    >>> doc = nlp(u'ITP is a two-year graduate program located in the Tisch School of the Arts. Perhaps the best way to describe us is as a Center for the Recently Possible.')
    >>> for np in doc.noun_chunks:
    ...   print(np.text)
    ... 
    ITP
    a two-year graduate program
    the Tisch School
    the Arts
    the best way
    us
    a Center