text: #!/usr/bin/env python3
  
  import spacy
  nlp = spacy.load("en_core_web_md")
  
  
  doc = nlp("She lived in NewHampshire.")
  print(len(doc))
  print([(token.text, token.lemma_, token.i) for token in doc])
  for token in doc:
      print(token.text, token.pos_, token.tag_, token.dep_)
  
  with doc.retokenize() as retokenizer:
      heads = [(doc[3], 1), doc[2]]
      attrs = {"TAG":["NNP", "NNP"], "DEP":["compound", "pobj"]}
      retokenizer.split(doc[3], ["New", "Hampshire"], heads=heads, attrs=attrs)
  
  
  print(len(doc))
  print([(token.text, token.lemma_, token.i) for token in doc])
  for token in doc:
      print(token.text, token.pos_, token.tag_, token.dep_)
  