code: def zip_flair_result(pred, tag_type="upos-fast"):
      """Takes a sentence tagging from `flair` and returns two lists, of words
      and their corresponding parts-of-speech."""
      from flair.data import Sentence
  
      if not isinstance(pred, Sentence):
          raise TypeError(
              "Result from Flair POS tagger must be a `Sentence` object."
          )
  
      tokens = pred.tokens
      word_list = []
      pos_list = []
      for token in tokens:
          word_list.append(token.text)
          if "pos" in tag_type:
              pos_list.append(token.annotation_layers["upos"][0]._value)
          elif tag_type == "ner":
              pos_list.append(token.get_label("ner"))
  
      return word_list, pos_list
  
imports: import re
  import string
  import flair
  import jieba
  from .importing import LazyLoader
label_desc: Use image node_id 11 for calling a global function with example usage: zip_flair_result(pred, tag_type) and returns: word_list,  pos_list