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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
id: string
category: string
question: string
scoring_rubric: struct<objective_satisfied: bool, quaestro_locked: bool, exit_reason: string, min_segments: int64, q (... 69 chars omitted)
  child 0, objective_satisfied: bool
  child 1, quaestro_locked: bool
  child 2, exit_reason: string
  child 3, min_segments: int64
  child 4, quaestro_last_result_contains: string
  child 5, trap_codes: list<item: string>
      child 0, item: string
to
{'id': Value('string'), 'category': Value('string'), 'question': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              category: string
              question: string
              scoring_rubric: struct<objective_satisfied: bool, quaestro_locked: bool, exit_reason: string, min_segments: int64, q (... 69 chars omitted)
                child 0, objective_satisfied: bool
                child 1, quaestro_locked: bool
                child 2, exit_reason: string
                child 3, min_segments: int64
                child 4, quaestro_last_result_contains: string
                child 5, trap_codes: list<item: string>
                    child 0, item: string
              to
              {'id': Value('string'), 'category': Value('string'), 'question': Value('string')}
              because column names don't match

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Challenge: Replicate the SOPHUS Defense

If scaling laws are sufficient to police algebraic hallucination, this corpus is where you prove it.

This release packages the Quaestro Bombardment-200 challenge: two hundred adversarially structured prompts spanning valid Lie-superalgebra intents and Fail-Closed trap classes, together with the Key–Value answer targets extracted under the SOPHUS dual-control architecture (typed constitution + residual excision) on a 9B-class model.

SOPHUS closed this split under the author's protocol at Intent Accuracy 200/200, with Fail-Closed exits on every trap row and zero budget_exhausted outcomes. The extraction machinery is not shipped here. The theoretical and systems methodology is published as Bona Sapiens Technical Report BS-7:

Sophus: Constrained Generation for Verified Algebra
DOI: 10.5281/zenodo.21712705

The challenge

Reproduce, by any means you prefer—frontier parameter count, long context, tool use, RLHF, constitutional AI, or prompt alchemy—both of the following on all 200 items:

  1. Defense: constitutionally admissible intents lock; every trap Fail-Closes (no fluent improvisation past the algebraic boundary; no wall-clock budget collapse substituted for typed refusal).
  2. Extraction: recover the SOPHUS Key–Value targets for the admissible sector (see sophus_kv_target.jsonl).

We do not provide the C++ orchestrator, residual forge, or intercept lattice. We provide the problems, the targets, and a public whitepaper. If scale alone solves verifiable algebra, the leaderboard writes itself.

Files

File Role
quaestro_200.jsonl Challenge inputs: id, category, question, scoring_rubric
sophus_kv_target.jsonl SOPHUS reference targets: lock/Fail-Closed labels, quaestro_last_result, and extracted kv_segments
README.md This card

Rules of engagement

  • Cite the Zenodo report when you publish attempts, successes, or partial closures.
  • Report protocol clearly: model, decoding, tools, wall-clock budget, and how you score “Fail-Closed” versus soft refusal.
  • Partial credit is welcome; 100/100 defense plus target extraction is the bar SOPHUS already cleared on this split under the stated harness.
  • This is an author-controlled corpus and scoring surface, not a claim of universal fixed points or external SOTA rankings.

Citation

@misc{kim2026sophus,
  author = {Kim, In-Gee},
  title  = {Sophus: Constrained Generation for Verified Algebra},
  year   = {2026},
  doi    = {10.5281/zenodo.21712705},
  url    = {https://doi.org/10.5281/zenodo.21712705},
  note   = {Bona Sapiens, Inc. Technical Report (BS-7)},
}

Dataset: bonasapiensinc/Quaestro-Bombardment-200.

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