code: def runTest(self):
      document_assembler = (
          DocumentAssembler()
          .setInputCol("text")
          .setOutputCol("document")
      )
      sentence_detector = (
          SentenceDetector()
          .setInputCols(["document"])
          .setOutputCol("sentence")
      )
      tokenizer = (
          Tokenizer().setInputCols(["sentence"]).setOutputCol("token")
      )
      pos_tagger = (
          PerceptronApproach()
          .setInputCols(["token", "sentence"])
          .setOutputCol("pos")
          .setIterations(3)
          .fit(self.train_pos)
      )
      chunker = (
          Chunker()
          .setInputCols(["sentence", "pos"])
          .setOutputCol("chunk")
          .setRegexParsers(["<NNP>+", "<DT|PP\\$>?<JJ>*<NN>"])
      )
      assembled = document_assembler.transform(self.data)
      sentenced = sentence_detector.transform(assembled)
      tokenized = tokenizer.fit(sentenced).transform(sentenced)
      pos_sentence_format = pos_tagger.transform(tokenized)
      chunk_phrases = chunker.transform(pos_sentence_format)
      chunk_phrases.show()
  
file_path: spark-nlp/python/test/annotator/chunker_test.py
imports: import os
  import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.util import SparkContextForTest
label_desc: Use image node_id 2 for calling the ChunkerTestSpec obj's underlying member method code with example usage: obj.runTest() without return types