code: def doc(en_tokenizer):
      # fmt: off
      text = "This is a sentence. This is another sentence. And a third."
      heads = [1, 1, 3, 1, 1, 6, 6, 8, 6, 6, 12, 12, 12, 12]
      deps = ["nsubj", "ROOT", "det", "attr", "punct", "nsubj", "ROOT", "det",
              "attr", "punct", "ROOT", "det", "npadvmod", "punct"]
      ents = ["O", "O", "B-ENT", "I-ENT", "I-ENT", "I-ENT", "I-ENT", "O", "O",
              "O", "O", "O", "O", "O"]
      # fmt: on
      tokens = en_tokenizer(text)
      lemmas = [
          t.text for t in tokens
      ]  # this is not correct, just a placeholder
      spaces = [bool(t.whitespace_) for t in tokens]
      return Doc(
          tokens.vocab,
          words=[t.text for t in tokens],
          spaces=spaces,
          heads=heads,
          deps=deps,
          ents=ents,
          lemmas=lemmas,
      )
  
imports: import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from thinc.api import get_current_ops
  from spacy.attrs import LENGTH, ORTH
  from spacy.lang.en import English
  from spacy.tokens import Doc, Span, Token
  from spacy.util import filter_spans
  from spacy.vocab import Vocab
  from ..util import add_vecs_to_vocab
  from .test_underscore import clean_underscore
label_desc: Use image node_id 1 for calling a global function with example usage: doc(en_tokenizer) and returns: Doc