>>> import benepar, spacy
>>> nlp = spacy.load('en_core_web_md')
>>> if spacy.__version__.startswith('2'):
nlp.add_pipe(benepar.BeneparComponent("benepar_en3"))
else:
nlp.add_pipe("benepar", config={"model": "benepar_en3"})
>>> doc = nlp("The time for action is now. It's never too late to do something.")
>>> sent = list(doc.sents)[0]
>>> print(sent._.parse_string)
(S (NP (NP (DT The) (NN time)) (PP (IN for) (NP (NN action)))) (VP (VBZ is) (ADVP (RB now))) (. .))
Thanks for your nice work. Is this model possible to be plugged into the spaCy NLP pipeline?
Something similar to this Berkley Neural Parser package?