code: def runTest(self):
      documentAssembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
      tokenizer = (
          Tokenizer().setInputCols(["document"]).setOutputCol("token")
      )
      embeddings = (
          WordEmbeddingsModel.pretrained()
          .setInputCols(["document", "token"])
          .setOutputCol("bert")
      )
      nerTagger = (
          NerDLModel.pretrained()
          .setInputCols(["document", "token", "bert"])
          .setOutputCol("ner")
      )
      pipeline = Pipeline().setStages(
          [documentAssembler, tokenizer, embeddings, nerTagger]
      )
      data = SparkSessionForTest.spark.createDataFrame(
          [["U.N. official Ekeus heads for Baghdad."]]
      ).toDF("text")
      result = pipeline.fit(data).transform(data)
  
      converter = (
          NerConverter()
          .setInputCols(["document", "token", "ner"])
          .setOutputCol("entities")
          .setPreservePosition(False)
          .setWhiteList(["ORG", "LOC"])
      )
  
      converter.transform(result).selectExpr("explode(entities)").show(
          truncate=False
      )
  
imports: import unittest
  import pytest
  from pyspark.ml import Pipeline
  from sparknlp.annotator import *
  from test.util import SparkSessionForTest
label_desc: Use image node_id 1 for calling the NerConverterTestSpec obj's underlying member method code with example usage: obj.runTest() without return types