code: def preprocess_ubuntu_corpus(df):
      
      statements = []
      replies = []
      for i, record in tqdm(df.iterrows()):
          turns = list(split_turns(record.Context))
          statement = turns[-1] if len(turns) else '\n'  # <1>
          statements.append(statement)
          turns = list(split_turns(record.Utterance))
          reply = turns[-1] if len(turns) else '\n'
          replies.append(reply)
      df['statement'] = statements
      df['reply'] = replies
      return df
docs: Split all strings in df.Context and df.Utterance on __eot__ (turn) markers