class_docstr: Convert evaluate result json to DataFrame for report generator,
  and analysis model robustness according to linguistic classification.
  
  Example::
  
      {
          "model_name": "BERT",
          "dataset_name": "medical data",
          "transformation": {
              "Case": {
                  "ori_precision": 0.70,
                  "trans_precision": 0.65,
                  "ori_f1": 0.63,
                  "trans_f1": 0.60,
                  "size": 5000,
              },
              "Ocr": {
                  "ori_precision": 0.72,
                  "trans_precision": 0.43,
                  "ori_f1": 0.62,
                  "trans_f1": 0.41,
                  "size": 5000,
              }
          },
          "subpopulation": {
              "LengthLengthSubPopulation-0.0-0.1": {
                  "trans_precision": 0.68,
                  "trans_f1": 0.63,
                  "size": 500
              }
          },
          "attack": {
              "Bert-Attack": {
                  "ori_precision": 0.72,
                  "trans_precision": 0.43,
                  "ori_f1": 0.62,
                  "trans_f1": 0.41,
                  "size": 400,
              }
          }
      }
docstr: Find linguistic classification of given transformation,
  if not found, return Other label.
  
  :param str transformation_str: transformation name
  :return: str linguistic classification name
docstr_tok: ["Find","linguistic","classification","of","given","transformation",",","if","not","found",",","return","Other","label",".",":","param","str","transformation_str",":","transformation","name",":","return",":","str","linguistic","classification","name"]
code: def get_parent(transformation_str):
      """
      Find linguistic classification of given transformation,
      if not found, return Other label.
  
      :param str transformation_str: transformation name
      :return: str linguistic classification name
  
      """
      parent = "Other"
  
      for category_type in CATEGORY:
          if transformation_str in CATEGORY[category_type]:
              parent = category_type
              break
  
      return parent
  
imports: import pandas
  import numpy
  from functools import reduce
  from copy import deepcopy
  from collections import OrderedDict
  from ...common.utils import logger
label_desc: Use image node_id 4 for calling the Analyzer obj's underlying member method code with example usage: obj.get_parent(transformation_str) and returns: parent