code: def get_data():
      sample = {
          "text_snippet": [
              "EU rejects German call to boycott British lamb .",
              "Peter Blackburn",
              "He said further scientific study was required and if it was found that action was needed it should be taken by the European Union .",
              ".",
              "It brought in 4,275 tonnes of British mutton , some 10 percent of overall imports .",
          ],
          "entity_annotations": [
              '[{"entity_group": "B-ORG", "start": 0, "end": 2}, {"entity_group": "B-MISC", "start": 11, "end": 17}, {"entity_group": "B-MISC", "start": 34, "end": 41}]',
              '[{"entity_group": "B-PER", "start": 0, "end": 5}, {"entity_group": "I-PER", "start": 6, "end": 15}]',
              '[{"entity_group": "B-ORG", "start": 115, "end": 123}, {"entity_group": "I-ORG", "start": 124, "end": 129}]',
              "[]",
              '[{"entity_group": "B-MISC", "start": 30, "end": 37}]',
          ],
      }
      return pd.DataFrame.from_dict(sample)
  
file_path: autogluon/multimodal/tests/unittests/others/test_ner.py
imports: import os
  import shutil
  import tempfile
  from unittest import mock
  import numpy.testing
  import pandas
  import pytest
  import torch
  from ray import tune
  from autogluon.multimodal import MultiModalPredictor
  from ..utils.utils import get_home_dir
label_desc: Use image node_id 1 for calling a global function with example usage: get_data() and returns: pd