class_docstr: Teacher which contains the question as the text, the sentences as the label
  candidates, and the label as the sentence containing the answer.
  
  Some punctuation may be removed for tokenization purposes.
class_docstr_tok: ["Teacher","which","contains","the","question","as","the","text",",","the","sentences","as","the","label","candidates",",","and","the","label","as","the","sentence","containing","the","answer",".","Some","punctuation","may","be","removed","for","tokenization","purposes","."]
code: def __init__(self, opt, shared=None):
      super().__init__(opt, shared)
  
      try:
          import nltk
      except ImportError:
          raise ImportError(
              "Please install nltk (e.g. pip install nltk)."
          )
      # nltk-specific setup
      st_path = "tokenizers/punkt/{0}.pickle".format("english")
      try:
          self.sent_tok = nltk.data.load(st_path)
      except LookupError:
          nltk.download("punkt")
          self.sent_tok = nltk.data.load(st_path)
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.teachers import FixedDialogTeacher, DialogTeacher
  from parlai.utils.io import PathManager
  from .build import build
  import json
  import os
label_desc: Use image node_id 1 to create a new SentenceLabelsTeacher object from inherited base classes: IndexTeacher with example: obj = SentenceLabelsTeacher(opt, shared)