code: def test_run(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
  
      sentence_detector = (
          SentenceDetector()
          .setInputCols(["document"])
          .setOutputCol("sentences")
      )
  
      tokenizer = (
          Tokenizer().setInputCols(["sentences"]).setOutputCol("tokens")
      )
  
      coref = self.tested_annotator
  
      pipeline = Pipeline(
          stages=[
              document_assembler,
              sentence_detector,
              tokenizer,
              coref,
          ]
      )
  
      model = pipeline.fit(self.data)
  
      model.transform(self.data).selectExpr(
          "explode(corefs) AS coref"
      ).selectExpr("coref.result as token", "coref.metadata").show(
          truncate=False
      )
  
file_path: spark-nlp/python/test/annotator/coref/spanbert_coref_test.py
imports: import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.annotator.common.has_max_sentence_length_test import HasMaxSentenceLengthTests
  from test.util import SparkSessionForTest
label_desc: Use image node_id 2 for calling the SpanBertCorefTestSpec obj's underlying member method code with example usage: obj.test_run() without return types