code: def test_label_ambiguity_condition():
      # Arrange
      data = {
          "col1": [1, 1, 1, 2, 2, 2] * 100,
          "col2": [1, 1, 1, 2, 2, 2] * 100,
          "col3": [1, 1, 1, 2, 2, 2] * 100,
          "label": [1, 1, 1, 1, 2, 1] * 100,
      }
      ds = Dataset(pd.DataFrame(data), label="label")
      check = (
          ConflictingLabels().add_condition_ratio_of_conflicting_labels_less_or_equal()
      )
  
      # Act
      result = check.run(ds)
      condition_result = check.conditions_decision(result)
  
      # Assert
      assert_that(
          condition_result,
          has_items(
              equal_condition_result(
                  is_pass=False,
                  details="Ratio of samples with conflicting labels: 50%",
                  name="Ambiguous sample ratio is less or equal to 0%",
              )
          ),
      )
  
file_path: deepchecks/tests/tabular/checks/integrity/conflicting_labels_test.py
imports: import pandas
  from hamcrest import assert_that, close_to, equal_to, has_entries, has_items, has_length, instance_of
  from deepchecks.tabular.checks.data_integrity import ConflictingLabels
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 5 for calling a global function with example usage: test_label_ambiguity_condition() without return types