code: def multilabel_dataset_without_conflicts():
      return TextData(
          label=[
              [1, 0, 0],
              [0, 0, 0],
              [0, 0, 1],
              [0, 0, 1],
              [0, 0, 0],
              [1, 0, 0],
          ],
          task_type="text_classification",
          raw_text=[
              "Explicit is better than implicit.",
              "Simple is better than complex.",
              "Readability counts.",
              "Readability counts to.",
              "Errors should never pass silently.",
              "Explicit, is better than implicit!",
          ],
      )
  
imports: import typing
  import pandas
  import pytest
  from hamcrest import *
  from deepchecks.nlp.checks import ConflictingLabels
  from deepchecks.nlp.text_data import TextData
  from deepchecks.utils.strings import format_percent
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 2 for calling a global function with example usage: multilabel_dataset_without_conflicts() and returns: TextData