code: def tagged_doc():
      text = "Sarah's sister flew to Silicon Valley via London."
      tags = [
          "NNP",
          "POS",
          "NN",
          "VBD",
          "IN",
          "NNP",
          "NNP",
          "IN",
          "NNP",
          ".",
      ]
      pos = [
          "PROPN",
          "PART",
          "NOUN",
          "VERB",
          "ADP",
          "PROPN",
          "PROPN",
          "ADP",
          "PROPN",
          "PUNCT",
      ]
      morphs = [
          "NounType=prop|Number=sing",
          "Poss=yes",
          "Number=sing",
          "Tense=past|VerbForm=fin",
          "",
          "NounType=prop|Number=sing",
          "NounType=prop|Number=sing",
          "",
          "NounType=prop|Number=sing",
          "PunctType=peri",
      ]
      nlp = English()
      doc = nlp(text)
      for i in range(len(tags)):
          doc[i].tag_ = tags[i]
          doc[i].pos_ = pos[i]
          doc[i].set_morph(morphs[i])
          if i > 0:
              doc[i].is_sent_start = False
      return doc
  
file_path: spacy/spacy/tests/test_scorer.py
imports: import pytest
  from numpy.testing import assert_almost_equal, assert_array_almost_equal
  from pytest import approx
  from spacy.lang.en import English
  from spacy.scorer import PRFScore, ROCAUCScore, Scorer, _roc_auc_score, _roc_curve
  from spacy.tokens import Doc, Span
  from spacy.training import Example
  from spacy.training.iob_utils import offsets_to_biluo_tags
label_desc: Use image node_id 1 for calling a global function with example usage: tagged_doc() and returns: doc