class_docstr: Label Encoder for the named entity recognition task.
class_docstr_tok: ["Label","Encoder","for","the","named","entity","recognition","task","."]
docstr: Transform raw JSON annotations to list annotations.
  
  Parameters
  ----------
  y
      The raw json annotations.
  
  Returns
  -------
  all_annotations
      A list of NER annotations.
docstr_tok: ["Transform","raw","JSON","annotations","to","list","annotations",".","Parameters","--","--","--","--","--","y","The","raw","json","annotations",".","Returns","--","--","--","-","all_annotations","A","list","of","NER","annotations","."]
code: def transform(self, y: pd.Series):
      """
      Transform raw JSON annotations to list annotations.
  
      Parameters
      ----------
      y
          The raw json annotations.
  
      Returns
      -------
      all_annotations
          A list of NER annotations.
      """
      all_annotations, _ = self.extract_ner_annotations(y)
      return all_annotations
  
imports: import json
  import logging
  import re
  from typing import Any, Dict, List, Optional, Union
  import jsonschema
  import numpy
  import pandas
  from omegaconf import DictConfig, OmegaConf
  from sklearn.preprocessing import LabelEncoder
  from ..constants import AUTOMM, END_OFFSET, ENTITY_GROUP, NER_ANNOTATION, PROBABILITY, START_OFFSET
label_desc: Use image node_id 4 for calling the NerLabelEncoder obj's underlying member method code with example usage: obj.transform(y) and returns: all_annotations