code: def test_concurrent_big():
      nlp = spacy.blank("en")
      nlp.add_pipe("dbpedia_spotlight", config={"verify_ssl": False})
      texts = [long_text] * 50 + [short_text] * 50
      docs = list(nlp.pipe(texts, batch_size=128))
      # check the order
      assert docs[0].ents, "document without entities"
      assert docs[1].ents, "document without entities"
      assert docs[0].text == long_text
      ents_counts = np.array([len(doc.ents) for doc in docs])
      print(ents_counts)
      assert ents_counts[:50].min() == ents_counts[:50].max()
      assert ents_counts[50:].min() == ents_counts[50:].max()
      assert ents_counts[0] == ents_counts[:50].mean()
      assert ents_counts[50] == ents_counts[50:].mean()
      assert ents_counts[0] > ents_counts[50]
  
file_path: spacy-dbpedia-spotlight/tests/test_extensive.py
imports: import spacy
  import numpy
label_desc: Use image node_id 12 for calling a global function with example usage: test_concurrent_big() without return types