code: def test_issue5458():
      # Test that the noun chuncker does not generate overlapping spans
      # fmt: off
      words = ["In", "an", "era", "where", "markets", "have", "brought", "prosperity", "and", "empowerment", "."]
      vocab = Vocab(strings=words)
      deps = ["ROOT", "det", "pobj", "advmod", "nsubj", "aux", "relcl", "dobj", "cc", "conj", "punct"]
      pos = ["ADP", "DET", "NOUN", "ADV", "NOUN", "AUX", "VERB", "NOUN", "CCONJ", "NOUN", "PUNCT"]
      heads = [0, 2, 0, 9, 6, 6, 2, 6, 7, 7, 0]
      # fmt: on
      en_doc = Doc(vocab, words=words, pos=pos, heads=heads, deps=deps)
      en_doc.noun_chunks_iterator = noun_chunks
  
      # if there are overlapping spans, this will fail with an E102 error "Can't merge non-disjoint spans"
      nlp = English()
      merge_nps = nlp.create_pipe("merge_noun_chunks")
      merge_nps(en_doc)
  
imports: import gc
  import numpy
  import pytest
  from thinc.api import get_current_ops
  import spacy
  from spacy.lang.en import English
  from spacy.lang.en.syntax_iterators import noun_chunks
  from spacy.language import Language
  from spacy.pipeline import TrainablePipe
  from spacy.tokens import Doc
  from spacy.training import Example
  from spacy.util import SimpleFrozenList, get_arg_names, make_tempdir
  from spacy.vocab import Vocab
label_desc: Use image node_id 8 for calling a global function with example usage: test_issue5458() without return types