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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
instruction: string
input: string
output: string
metadata: struct<topic: string, aligned_source: string, aligned_id: string, aligned_score: double, supporting_ (... 23 chars omitted)
  child 0, topic: string
  child 1, aligned_source: string
  child 2, aligned_id: string
  child 3, aligned_score: double
  child 4, supporting_count: int64
  child 5, v3: bool
attestation: struct<alg: string, pub: string, sig: string, digest: string, ts: timestamp[s]>
  child 0, alg: string
  child 1, pub: string
  child 2, sig: string
  child 3, digest: string
  child 4, ts: timestamp[s]
to
{'instruction': Value('string'), 'input': Value('string'), 'output': Value('string'), 'metadata': {'topic': Value('string'), 'aligned_source': Value('string'), 'aligned_id': Value('string'), 'aligned_score': Value('float64'), 'supporting_count': Value('int64'), 'v3': Value('bool')}}
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
              instruction: string
              input: string
              output: string
              metadata: struct<topic: string, aligned_source: string, aligned_id: string, aligned_score: double, supporting_ (... 23 chars omitted)
                child 0, topic: string
                child 1, aligned_source: string
                child 2, aligned_id: string
                child 3, aligned_score: double
                child 4, supporting_count: int64
                child 5, v3: bool
              attestation: struct<alg: string, pub: string, sig: string, digest: string, ts: timestamp[s]>
                child 0, alg: string
                child 1, pub: string
                child 2, sig: string
                child 3, digest: string
                child 4, ts: timestamp[s]
              to
              {'instruction': Value('string'), 'input': Value('string'), 'output': Value('string'), 'metadata': {'topic': Value('string'), 'aligned_source': Value('string'), 'aligned_id': Value('string'), 'aligned_score': Value('float64'), 'supporting_count': Value('int64'), 'v3': Value('bool')}}
              because column names don't match

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OOWM Ground Truth v3 — Mined + Aligned

This is the v3 of the OOWM ground-truth dataset, built per the user's directive:

"mine all we have testing and improving existing"

What changed from v2

  • v2: 58 docs from 4 sources (Claude API + arXiv + Kimi + GitHub), 16 topics
  • v3: 1,147 docs from 5 sources (v2 + mined existing SFT/eval/refusal data), 32 topics
  • Mined: 1,089 docs from /root/care_sft_*.jsonl, /root/gov_sft_*.jsonl, /workspace/refusal_*.jsonl, /root/clawd/_alignment/SOV_SIGNAL/*.jsonl
  • Topics expanded from 16 to 32 — added risk-specific: refusal policy, care ethics, EU AI Act risk tier, PII handling, etc.
  • Zero weak topics (all 32 topics have ≥ 5 supporting cross-source docs)

Sources

{
  "existing_mine": 1089,
  "claude": 21,
  "kimi": 20,
  "science": 12,
  "github": 5
}

Pipeline

  1. mine_oowm.py — extracted 1,089 docs from existing RunPod SFT/eval/refusal assets
  2. align_v3.py — cross-source TF-IDF + BFT consensus on 32 topics
  3. train_v3.py (this script) — builds instruction-tuning corpus + Ed25519 signs + uploads

Stats

  • 32 instruction-tuning rows
  • 32 topics aligned across 5 sources
  • All rows Ed25519-signed
  • Honest: 1 receipt, 2 surface sprays (HF + Kaggle) per spray_v3 flow

Provenance

  • Generated on RunPod pod sov-brain-2 (RTX 3090, 24GB)
  • Pod id: dxjgtj2jyvljxo
  • Built: 2026-08-08T10:19:23Z
  • 4-source ingest: Claude, science (arXiv), Kimi (Moonshot API), GitHub
  • 5th source: existing sovereign SFT/eval/refusal data on RunPod

License

Apache-2.0.

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