class_docstr: Transform the sentence containing answer with AlterSentence transformation.
  
  Example::
  
      origin sentence: Denver Broncos defeated the National Football
          Conference champion Carolina Panthers 24–10 to earn their
          third Super Bowl title.
      transformed sentence: Denver Broncos defeated the National Football
          Conference champ Carolina Panthers 24–10 to earn
          their 3rd Super Bowl rubric.
class_docstr_tok: ["Transform","the","sentence","containing","answer","with","AlterSentence","transformation",".","Example",":",":","origin","sentence",":","Denver","Broncos","defeated","the","National","Football","Conference","champion","Carolina","Panthers","24\u201310","to","earn","their","third","Super","Bowl","title",".","transformed","sentence",":","Denver","Broncos","defeated","the","National","Football","Conference","champ","Carolina","Panthers","24\u201310","to","earn","their","3rd","Super","Bowl","rubric","."]
code: def __repr__(self):
      return "PerturbAnswer"
  
file_path: textflint/textflint/generation/transformation/MRCCN/perturb_answer.py
imports: from copy import deepcopy
  from ....common.settings import ORIGIN
  from ..transformation import Transformation
  from ....common.settings import CN_EMBEDDING_PATH
  from ....common.utils.load import json_lines_loader
  from ....common.utils.install import download_if_needed
label_desc: Use image node_id 2 for calling the PerturbAnswer obj's underlying member method code with example usage: obj.__repr__() and returns: str