class_docstr: Filter samples based on gender bias
  
  for example in mode 'man'::
  
      sample 1: "There is a boy.", score: 1
      sample 2: "There is a girl.", score: 1
      sample 3: "There are boys and girls.", score: 0
code: def word_match(self, texts, type):
      for text in texts:
          if type == "man":
              result = self.processor.extract_keywords(text)
              if "man" in result:
                  return True
          else:
              result = self.processor.extract_keywords(text)
              if "woman" in result:
                  return True
      return False
  
file_path: textflint/textflint/generation/subpopulation/UT/prejudice.py
imports: from flashtext import KeywordProcessor
  from ..subpopulation import SubPopulation
  from ....common.settings import PREJUDICE_PATH
  from ....common.utils.install import download_if_needed
  from ....common.utils.file_io import read_json
label_desc: Use image node_id 5 for calling the PrejudiceSubPopulation obj's underlying member method code with example usage: obj.word_match(texts, type) and returns: False, True, True