class_docstr: Search Query teacher.
  
  Given an input context, predict the title of the document from which the "gold"
  knowledge is derived.
class_docstr_tok: ["Search","Query","teacher",".","Given","an","input","context",",","predict","the","title","of","the","document","from","which","the","``","gold","''","knowledge","is","derived","."]
code: def _clean_text(self, txt, label):
      PRFX = "<doc>"
      if txt.startswith(PRFX):
          # removing the extra white-space character after the PRFX too.
          txt = txt[len(PRFX) + 1 :]
  
      if self._rem_possible_title:
          txt = remove_possible_title_from_text(txt, label)
  
      if (
          self._random_trim_min_len > 0
          and len(txt) > self._random_trim_min_len
      ):
          trim_point_idx = random.randint(
              0, len(txt) - self._random_trim_min_len
          )
          txt = txt[trim_point_idx:]
  
      return txt
  
imports: from abc import ABC, abstractmethod
  import os
  from typing import Tuple, List, Optional, Any, Dict
  import random
  from parlai.core.message import Message
  from parlai.core.metrics import F1Metric, BleuMetric, RougeMetric, AverageMetric, ExactMatchMetric, normalize_answer
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.teachers import ChunkTeacher, ChunkOutput
  import parlai.tasks.wizard_of_internet.constants
  from parlai.utils.conversations import Conversations
  from parlai.utils.data import DatatypeHelper
  import parlai.utils.logging
  from parlai.tasks.wizard_of_wikipedia.agents import TOKEN_KNOWLEDGE, TOKEN_END_KNOWLEDGE
  from projects.seeker.utils import extract_entities, remove_possible_title_from_text
label_desc: Use image node_id 3 for calling the SearchQueryTeacher obj's underlying member method code with example usage: obj._clean_text(txt, label) and returns: txt