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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
version: string
outcomes: list<item: struct<outcome_id: string, label: string, order: int64, definition: string, detection_sta (... 60 chars omitted)
  child 0, item: struct<outcome_id: string, label: string, order: int64, definition: string, detection_stage: string, (... 48 chars omitted)
      child 0, outcome_id: string
      child 1, label: string
      child 2, order: int64
      child 3, definition: string
      child 4, detection_stage: string
      child 5, failure_class: string
      child 6, example_case_id: string
definition: string
label: string
order: int64
detection_stage: string
example_case_id: string
failure_class: string
outcome_id: string
to
{'outcome_id': Value('string'), 'label': Value('string'), 'order': Value('int64'), 'definition': Value('string'), 'detection_stage': Value('string'), 'failure_class': Value('string'), 'example_case_id': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              version: string
              outcomes: list<item: struct<outcome_id: string, label: string, order: int64, definition: string, detection_sta (... 60 chars omitted)
                child 0, item: struct<outcome_id: string, label: string, order: int64, definition: string, detection_stage: string, (... 48 chars omitted)
                    child 0, outcome_id: string
                    child 1, label: string
                    child 2, order: int64
                    child 3, definition: string
                    child 4, detection_stage: string
                    child 5, failure_class: string
                    child 6, example_case_id: string
              definition: string
              label: string
              order: int64
              detection_stage: string
              example_case_id: string
              failure_class: string
              outcome_id: string
              to
              {'outcome_id': Value('string'), 'label': Value('string'), 'order': Value('int64'), 'definition': Value('string'), 'detection_stage': Value('string'), 'failure_class': Value('string'), 'example_case_id': Value('string')}
              because column names don't match

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Dali Verification Taxonomy

Five verification outcomes used by Dali to classify legal AI citation failures.

Citation failures are not binary. Link checkers return valid or broken. Legal AI failures require classification that separates what broke from why it broke.

Outcomes

ID Label Detection stage
verified Verified existence_and_support
authority_not_found Authority Not Found existence
proposition_unsupported Proposition Unsupported support
source_trail_missing Source Trail Missing evidence_preservation
unverifiable Unverifiable evidence_preservation

Files

  • taxonomy.json — full taxonomy document
  • outcomes.jsonl — one row per outcome for programmatic use

Engineering note

  • Outcomes 2 and 3 require different detection pipelines
  • Outcomes 4 and 5 are evidence preservation failures, not model failures
  • Outcome 1 still requires a sealed bundle — correctness without provenance is not defensible

Related resources

Citation

@dataset{yenklabs_dali_verification_taxonomy_2026,
  title={Dali Verification Taxonomy},
  author={YenkLabs},
  year={2026},
  url={https://huggingface.co/datasets/yenklabs/dali-verification-taxonomy}
}
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