text: import json
  from spacy.lang.en import English
  from spacy.tokens import Doc
  
  with open("exercises/en/bookquotes.json") as f:
      DATA = json.loads(f.read())
  
  nlp = English()
  
  # Register the Doc extension "author" (default None)
  Doc.set_extension("author", default=None)
  
  # Register the Doc extension "book" (default None)
  Doc.set_extension("book", default=None)
  
  for doc, context in nlp.pipe(DATA, as_tuples=True):
      # Set the doc._.book and doc._.author attributes from the context
      doc._.book = context["book"]
      doc._.author = context["author"]
  
      # Print the text and custom attribute data
      print(f"{doc.text}\n — '{doc._.book}' by {doc._.author}\n")
  