nestor/resources/spacy_ex.py

import fr_core_news_sm

nlp = fr_core_news_sm.load()
doc = nlp(u"Salut c'est nous! On revient de Paris.")

for token in doc:
    print(token.text, token.lemma_, token.pos_, token.tag_, token.dep_,
          token.shape_, token.is_alpha, token.is_stop)

for ent in doc.ents:
    print(ent.text, ent.start_char, ent.end_char, ent.label_)