code: def test_empty_ner():
      nlp = English()
      ner = nlp.add_pipe("ner")
      ner.add_label("MY_LABEL")
      nlp.initialize()
      doc = nlp("John is watching the news about Croatia's elections")
      # if this goes wrong, the initialization of the parser's upper layer is probably broken
      result = ["O", "O", "O", "O", "O", "O", "O", "O", "O"]
      assert [token.ent_iob_ for token in doc] == result
  
imports: import logging
  import random
  import pytest
  from numpy.testing import assert_equal
  from spacy import registry, util
  from spacy.attrs import ENT_IOB
  from spacy.lang.en import English
  from spacy.lang.it import Italian
  from spacy.language import Language
  from spacy.lookups import Lookups
  from spacy.pipeline import EntityRecognizer
  from spacy.pipeline._parser_internals.ner import BiluoPushDown
  from spacy.pipeline.ner import DEFAULT_NER_MODEL
  from spacy.tokens import Doc, Span
  from spacy.training import Example, iob_to_biluo, split_bilu_label
  from spacy.vocab import Vocab
  from ..util import make_tempdir
label_desc: Use image node_id 26 for calling a global function with example usage: test_empty_ner() without return types