code: def _get_table_from_mr(mr):
      """Converts a meaningful representation from e2e_cleaned dataset in a table."""
      mr_as_table = []
      for type_value in mr.split(", "):
          type_value_delimiter = type_value.find("[")
          type_ = type_value[0:type_value_delimiter]
          value = type_value[type_value_delimiter + 1 : -1]
          mr_as_table.append(
              {
                  "column_header": type_,
                  "row_number": 1,
                  "content": value,
              }
          )
      return mr_as_table
  
file_path: datasets/tensorflow_datasets/datasets/e2e_cleaned/e2e_cleaned_dataset_builder.py
imports: from __future__ import annotations
  import csv
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling a global function with example usage: _get_table_from_mr(mr) and returns: mr_as_table