class_docstr: OneCommon teacher that loads the data from https://github.com/Alab-NII/Reference-
  Resolution.
class_docstr_tok: ["OneCommon","teacher","that","loads","the","data","from","https",":","\/\/github.com\/Alab-NII\/Reference-","Resolution","."]
code: def _split_dialogue(self, words, separator=EOS_TOKEN):
      sentences = []
      spans = []
      start = 0
      for stop in range(len(words)):
          if words[stop] == separator:
              sentences.append(words[start:stop])
              spans.append((start, stop))
              start = stop + 1
      if stop >= start:
          sentences.append(words[start:])
          spans.append((start, len(words) - 1))
  
      # Dataset contains consecutive turn
      # concatenate utterances for those cases
      dialogue = []
      utterance = sentences[0]
      for i in range(1, len(sentences)):
          if sentences[i - 1][0] == sentences[i][0]:
              utterance += sentences[i][1:]
          else:
              dialogue.append(utterance)
              utterance = sentences[i]
      dialogue.append(utterance)
  
      if dialogue[0][0] == YOU_TOKEN:
          # Dialogue starts with YOU
          dialogue.insert(0, None)
          spans.insert(0, None)
      if dialogue[-1][0] == THEM_TOKEN:
          # Dialogue starts with THEM
          dialogue.append(None)
          spans.append(None)
  
      return dialogue, spans
  
file_path: ParlAI/parlai/tasks/onecommon/agents.py
imports: from parlai.core.teachers import FixedDialogTeacher
  from parlai.utils.io import PathManager
  from .build import build
  import os
label_desc: Use image node_id 9 for calling the OneCommonTeacher obj's underlying member method code with example usage: obj._split_dialogue(words, separator) and returns: dialogue,  spans