Datasets:

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Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
source_id: string
study_group: string
task_type: string
audience: string
instruction: string
length_guidance: string
evidence: list<item: struct<evidence_id: string, text: string, locator: string>>
  child 0, item: struct<evidence_id: string, text: string, locator: string>
      child 0, evidence_id: string
      child 1, text: string
      child 2, locator: string
target_answer: string
answer_evidence_map: list<item: struct<claim: string, evidence_ids: list<item: string>>>
  child 0, item: struct<claim: string, evidence_ids: list<item: string>>
      child 0, claim: string
      child 1, evidence_ids: list<item: string>
          child 0, item: string
quality_notes: list<item: string>
  child 0, item: string
schema_version: string
split: string
provenance: struct<draft_origin: string, human_author_review: string, expert_approval: bool>
  child 0, draft_origin: string
  child 1, human_author_review: string
  child 2, expert_approval: bool
review: struct<structural_validation: string, independent_ai_evidence_review: string, human_review: string,  (... 25 chars omitted)
  child 0, structural_validation: string
  child 1, independent_ai_evidence_review: string
  child 2, human_review: string
  child 3, ready_for_training: bool
source_ref: string
messages: list<item: struct<role: string, content: string>>
  child 0, item: struct<role: string, content: string>
      child 0, role: string
      child 1, content: string
to
{'messages': List({'role': Value('string'), 'content': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              source_id: string
              study_group: string
              task_type: string
              audience: string
              instruction: string
              length_guidance: string
              evidence: list<item: struct<evidence_id: string, text: string, locator: string>>
                child 0, item: struct<evidence_id: string, text: string, locator: string>
                    child 0, evidence_id: string
                    child 1, text: string
                    child 2, locator: string
              target_answer: string
              answer_evidence_map: list<item: struct<claim: string, evidence_ids: list<item: string>>>
                child 0, item: struct<claim: string, evidence_ids: list<item: string>>
                    child 0, claim: string
                    child 1, evidence_ids: list<item: string>
                        child 0, item: string
              quality_notes: list<item: string>
                child 0, item: string
              schema_version: string
              split: string
              provenance: struct<draft_origin: string, human_author_review: string, expert_approval: bool>
                child 0, draft_origin: string
                child 1, human_author_review: string
                child 2, expert_approval: bool
              review: struct<structural_validation: string, independent_ai_evidence_review: string, human_review: string,  (... 25 chars omitted)
                child 0, structural_validation: string
                child 1, independent_ai_evidence_review: string
                child 2, human_review: string
                child 3, ready_for_training: bool
              source_ref: string
              messages: list<item: struct<role: string, content: string>>
                child 0, item: struct<role: string, content: string>
                    child 0, role: string
                    child 1, content: string
              to
              {'messages': List({'role': Value('string'), 'content': Value('string')})}
              because column names don't match