code: def normalize_empty_tags(sentences):
      """
      If any tags are None, _, -, or blank, turn them into EMPTY
  
      The input should be a list(sentence) of list(word) of tuple(text, list(tag))
      which is the typical format for the data at the time data.py is preprocessing the tags
      """
      new_sentences = [
          [
              (
                  word[0],
                  tuple(
                      EMPTY if x in EMPTY_TAG else x for x in word[1]
                  ),
              )
              for word in sentence
          ]
          for sentence in sentences
      ]
      return new_sentences
  
file_path: stanza/stanza/models/ner/utils.py
imports: import logging
  from stanza.models.common.vocab import EMPTY
label_desc: Use image node_id 6 for calling a global function with example usage: normalize_empty_tags(sentences) and returns: new_sentences