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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
matrix_id: string
id: string
synthetic: bool
weights: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
  child 0, quality: int64
  child 1, speed: int64
  child 2, cost: int64
  child 3, flexibility: int64
  child 4, governance: int64
expected_winner_id: string
result: struct<ok: bool, winner_id: string, scores: list<item: struct<option_id: string, score: double>>>
  child 0, ok: bool
  child 1, winner_id: string
  child 2, scores: list<item: struct<option_id: string, score: double>>
      child 0, item: struct<option_id: string, score: double>
          child 0, option_id: string
          child 1, score: double
publisher: struct<name: string, website: string>
  child 0, name: string
  child 1, website: string
license: string
matrices: list<item: struct<id: string, title: struct<en: string, ru: string>, scope: struct<en: string, ru: s (... 505 chars omitted)
  child 0, item: struct<id: string, title: struct<en: string, ru: string>, scope: struct<en: string, ru: string>, pub (... 493 chars omitted)
      child 0, id: string
      child 1, title: struct<en: string, ru: string>
          child 0, en: string
          child 1, ru: string
      child 2, scope: struct<en: string, ru: string>
          child 0, en: string
          child 1, ru: string
      child 3, publisher: struct<name: string, website: string>
          child 0, name: string
          child 1, website: string
      child 4, criteria: list<item: struct<id: string, label: s
...
, ru: string>, ratings: struct<quality: int64, (... 68 chars omitted)
          child 0, item: struct<id: string, label: struct<en: string, ru: string>, ratings: struct<quality: int64, speed: int (... 56 chars omitted)
              child 0, id: string
              child 1, label: struct<en: string, ru: string>
                  child 0, en: string
                  child 1, ru: string
              child 2, ratings: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
                  child 0, quality: int64
                  child 1, speed: int64
                  child 2, cost: int64
                  child 3, flexibility: int64
                  child 4, governance: int64
      child 6, scenarios: list<item: struct<id: string, synthetic: bool, weights: struct<quality: int64, speed: int64, cost: i (... 74 chars omitted)
          child 0, item: struct<id: string, synthetic: bool, weights: struct<quality: int64, speed: int64, cost: int64, flexi (... 62 chars omitted)
              child 0, id: string
              child 1, synthetic: bool
              child 2, weights: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
                  child 0, quality: int64
                  child 1, speed: int64
                  child 2, cost: int64
                  child 3, flexibility: int64
                  child 4, governance: int64
              child 3, expected_winner_id: string
schema_version: string
to
{'schema_version': Value('string'), 'publisher': {'name': Value('string'), 'website': Value('string')}, 'license': Value('string'), 'matrices': List({'id': Value('string'), 'title': {'en': Value('string'), 'ru': Value('string')}, 'scope': {'en': Value('string'), 'ru': Value('string')}, 'publisher': {'name': Value('string'), 'website': Value('string')}, 'criteria': List({'id': Value('string'), 'label': {'en': Value('string'), 'ru': Value('string')}}), 'options': List({'id': Value('string'), 'label': {'en': Value('string'), 'ru': Value('string')}, 'ratings': {'quality': Value('int64'), 'speed': Value('int64'), 'cost': Value('int64'), 'flexibility': Value('int64'), 'governance': Value('int64')}}), 'scenarios': List({'id': Value('string'), 'synthetic': Value('bool'), 'weights': {'quality': Value('int64'), 'speed': Value('int64'), 'cost': Value('int64'), 'flexibility': Value('int64'), 'governance': Value('int64')}, 'expected_winner_id': 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/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/python3.14/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
              matrix_id: string
              id: string
              synthetic: bool
              weights: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
                child 0, quality: int64
                child 1, speed: int64
                child 2, cost: int64
                child 3, flexibility: int64
                child 4, governance: int64
              expected_winner_id: string
              result: struct<ok: bool, winner_id: string, scores: list<item: struct<option_id: string, score: double>>>
                child 0, ok: bool
                child 1, winner_id: string
                child 2, scores: list<item: struct<option_id: string, score: double>>
                    child 0, item: struct<option_id: string, score: double>
                        child 0, option_id: string
                        child 1, score: double
              publisher: struct<name: string, website: string>
                child 0, name: string
                child 1, website: string
              license: string
              matrices: list<item: struct<id: string, title: struct<en: string, ru: string>, scope: struct<en: string, ru: s (... 505 chars omitted)
                child 0, item: struct<id: string, title: struct<en: string, ru: string>, scope: struct<en: string, ru: string>, pub (... 493 chars omitted)
                    child 0, id: string
                    child 1, title: struct<en: string, ru: string>
                        child 0, en: string
                        child 1, ru: string
                    child 2, scope: struct<en: string, ru: string>
                        child 0, en: string
                        child 1, ru: string
                    child 3, publisher: struct<name: string, website: string>
                        child 0, name: string
                        child 1, website: string
                    child 4, criteria: list<item: struct<id: string, label: s
              ...
              , ru: string>, ratings: struct<quality: int64, (... 68 chars omitted)
                        child 0, item: struct<id: string, label: struct<en: string, ru: string>, ratings: struct<quality: int64, speed: int (... 56 chars omitted)
                            child 0, id: string
                            child 1, label: struct<en: string, ru: string>
                                child 0, en: string
                                child 1, ru: string
                            child 2, ratings: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
                                child 0, quality: int64
                                child 1, speed: int64
                                child 2, cost: int64
                                child 3, flexibility: int64
                                child 4, governance: int64
                    child 6, scenarios: list<item: struct<id: string, synthetic: bool, weights: struct<quality: int64, speed: int64, cost: i (... 74 chars omitted)
                        child 0, item: struct<id: string, synthetic: bool, weights: struct<quality: int64, speed: int64, cost: int64, flexi (... 62 chars omitted)
                            child 0, id: string
                            child 1, synthetic: bool
                            child 2, weights: struct<quality: int64, speed: int64, cost: int64, flexibility: int64, governance: int64>
                                child 0, quality: int64
                                child 1, speed: int64
                                child 2, cost: int64
                                child 3, flexibility: int64
                                child 4, governance: int64
                            child 3, expected_winner_id: string
              schema_version: string
              to
              {'schema_version': Value('string'), 'publisher': {'name': Value('string'), 'website': Value('string')}, 'license': Value('string'), 'matrices': List({'id': Value('string'), 'title': {'en': Value('string'), 'ru': Value('string')}, 'scope': {'en': Value('string'), 'ru': Value('string')}, 'publisher': {'name': Value('string'), 'website': Value('string')}, 'criteria': List({'id': Value('string'), 'label': {'en': Value('string'), 'ru': Value('string')}}), 'options': List({'id': Value('string'), 'label': {'en': Value('string'), 'ru': Value('string')}, 'ratings': {'quality': Value('int64'), 'speed': Value('int64'), 'cost': Value('int64'), 'flexibility': Value('int64'), 'governance': Value('int64')}}), 'scenarios': List({'id': Value('string'), 'synthetic': Value('bool'), 'weights': {'quality': Value('int64'), 'speed': Value('int64'), 'cost': Value('int64'), 'flexibility': Value('int64'), 'governance': Value('int64')}, 'expected_winner_id': Value('string')})})}
              because column names don't match

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SHAR Production Option Matrices

This dataset by SHAR Production contains 100 deterministic synthetic preference scenarios for 25 bilingual interactive production option matrices. Each matrix compares three options using five adjustable criteria and returns a transparent ranked recommendation.

scenarios.jsonl contains synthetic weight profiles and deterministic ranked results. catalog.json contains the bilingual matrix, option and criterion definitions.

Synthetic scenarios and results use CC-BY-4.0. The source implementation and documentation use MIT.

No client data, media, credentials, analytics or performance claims are included. AI assistance was used to draft and validate the synthetic material under SHAR Production's publishing responsibility.

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