class_docstr: Use Bert to generate words.
  
  Example::
  
      小明喜欢看书 -> 小明喜欢看报纸
docstr: get the pos of sentence if we need
  
  :param str sentence: origin word
  :return: bool
docstr_tok: ["get","the","pos","of","sentence","if","we","need",":","param","str","sentence",":","origin","word",":","return",":","bool"]
code: def check_part_pos(sentence):
      """
      get the pos of sentence if we need
  
      :param str sentence: origin word
      :return: bool
      """
      if sentence == "":
          return False
      Processor = CnProcessor()
      pos = Processor.get_pos_tag(sentence)
      if len(pos) == 1 and pos[0][0] == "n":
          return True
      return False
  
file_path: textflint/textflint/generation/transformation/CWS/cn_mlm.py
imports: import torch
  from transformers import BertTokenizer, BertForMaskedLM
  from ..transformation import Transformation
  from ....input.component.field.cn_text_field import CnTextField
  from ....common.preprocess.cn_processor import CnProcessor
  from ....common.settings import ORIGIN, MODIFIED_MASK
label_desc: Use image node_id 8 for calling the CnMLM obj's underlying member method code with example usage: obj.check_part_pos(sentence) and returns: False, False, True