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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type string to null
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
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 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2118, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2014, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type string to null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
run_id string | arm string | split string | variant string | repetition int64 | model dict | environment dict | enforcement dict | corpus_hash string | catalogue_hash string | prompt_hash string | schema_hash string | scores list | calls dict | degradation unknown | selected unknown | document_chars int64 | links list | dangling list | unpinned list | invalid list | repairs int64 | notes string | training_match dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10004|r1 | A0-json | dev | native | 1 | {
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"platform": "Windows-11-10.0.26200-SP0",
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} | {
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... | {} | {} | 118 | [] | [] | [] | [] | 0 | corpus=wiki-measurements,dataset=Wiki-Measurements/raw/wiki-measurements_large_strict.json,doi=10.5281/zenodo.14858280,notation=written,licence=CC BY-SA 4.0 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10034|r1 | A0-json | dev | native | 1 | {
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... | {} | {} | 118 | [] | [] | [] | [] | 0 | corpus=wiki-measurements,dataset=Wiki-Measurements/raw/wiki-measurements_large_strict.json,doi=10.5281/zenodo.14858280,notation=written,licence=CC BY-SA 4.0 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10049|r1 | A0-json | dev | native | 1 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10140|r1 | A0-json | dev | native | 1 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10146|r1 | A0-json | dev | native | 1 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10249|r1 | A0-json | dev | native | 1 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10448|r1 | A0-json | dev | native | 1 | {
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A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10495|r1 | A0-json | dev | native | 1 | {
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"cached_input_tokens": 0,
"reasoning_tokens": 0,
"total_tokens": 129
... | {} | {} | 81 | [] | [] | [] | [] | 0 | corpus=wiki-measurements,dataset=Wiki-Measurements/raw/wiki-measurements_large_strict.json,doi=10.5281/zenodo.14858280,notation=written,licence=CC BY-SA 4.0 | {
"status": "base",
"differing": []
} |
A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10279|r1 | A0-json | dev | native | 1 | {
"model": "unsloth/Qwen3.5-4B",
"model_version": "1",
"provider_profile": "openai",
"region": null,
"temperature": 0,
"max_tokens": 1024,
"seed": null
} | {
"benchmark_version": "0.1.0",
"benchmark_sha": "local",
"oold_version": null,
"python_version": "3.13.1",
"platform": "Windows-11-10.0.26200-SP0",
"started_at": "2026-10-04T09:56:36.935821+00:00"
} | {
"arm": "A0-json",
"reasoning": "off",
"catalogue_size": 100,
"signal": "named",
"vocabulary": "consensus",
"language": null,
"unit_match": "exact",
"orchestration": "single_shot",
"shortlist_k": null,
"plan_retry": false,
"describe_catalogue": true,
"pin_units": true,
"output_form": "json"
} | b3dcb01b4cff42a9efd97b8a622650956431114616fa1eb895a5a808d9e87053 | 4ad2c7e472ab9c0e6d278fde494df2c7cd9f2bf9a85fb6b804918af73d90d56b | e0d088dee5d45af331fd1fe1c08d019776e2bf436f803d36ab5e5c9f6aeec54b | null | [
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"primary_f1": 0,
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"dimensions": {
"class": {
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"tp": 0,
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"fn": 1,
"support"... | {
"calls": [
{
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"model": "unsloth/Qwen3.5-4B",
"attempt": 1,
"elapsed_s": 3.1165,
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"input_tokens": 91,
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... | {} | {} | 150 | [] | [] | [] | [] | 0 | corpus=wiki-measurements,dataset=Wiki-Measurements/raw/wiki-measurements_large_strict.json,doi=10.5281/zenodo.14858280,notation=written,licence=CC BY-SA 4.0 | {
"status": "base",
"differing": []
} |
A0-json/named/consensus/n100/think:off|unsloth/Qwen3.5-4B|wm-10301|r1 | A0-json | dev | native | 1 | {
"model": "unsloth/Qwen3.5-4B",
"model_version": "1",
"provider_profile": "openai",
"region": null,
"temperature": 0,
"max_tokens": 1024,
"seed": null
} | {
"benchmark_version": "0.1.0",
"benchmark_sha": "local",
"oold_version": null,
"python_version": "3.13.1",
"platform": "Windows-11-10.0.26200-SP0",
"started_at": "2026-10-04T09:56:36.935821+00:00"
} | {
"arm": "A0-json",
"reasoning": "off",
"catalogue_size": 100,
"signal": "named",
"vocabulary": "consensus",
"language": null,
"unit_match": "exact",
"orchestration": "single_shot",
"shortlist_k": null,
"plan_retry": false,
"describe_catalogue": true,
"pin_units": true,
"output_form": "json"
} | 388005036e265418795aa9bd1def330d3a4eebb5daae861dc63cc1142cd38c4f | 4ad2c7e472ab9c0e6d278fde494df2c7cd9f2bf9a85fb6b804918af73d90d56b | ca52862d19b99604dd58a7893b0b7bd95482e6ca48f3c13310611467bccca435 | null | [
{
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... | {} | {} | 57 | [] | [] | [] | [] | 0 | corpus=wiki-measurements,dataset=Wiki-Measurements/raw/wiki-measurements_large_strict.json,doi=10.5281/zenodo.14858280,notation=written,licence=CC BY-SA 4.0 | {
"status": "base",
"differing": []
} |
End of preview.
oold-llm-bench results
9,837 graded cells from oold-llm-bench, one JSON object per line. Each says what the prompt carried, what the decoder would accept, what the model answered and what it scored on seven dimensions.
| condition | cells |
|---|---|
schema-prose-catalog-flat-enforced |
2,826 |
no-catalog-not-enforced |
1,678 |
no-catalog-enforced |
1,484 |
schema-prose-catalog-enforced |
1,075 |
schema-prose-full-catalog-enforced |
815 |
schema-dump-catalog-not-enforced-gated |
600 |
schema-dump-catalog-flat-enforced |
599 |
schema-prose-full-catalog-flat-enforced |
400 |
schema-dump-catalog-flat-enforced-strict |
360 |
Over 23 models, 18 runs.
What is not here
The reply itself. A record keeps the verbatim answer locally so a later grader fix can be applied without re-running a grid, and that text is page text whose licence is not ours to extend. The published variant is produced by an allowlist rather than by removing fields, so a field added later is withheld until somebody decides otherwise.
Reading a record
arm carries the internal id a run was written with. The published name is
composed from what the prompt carried and what the decoder accepted:
| in the record | published name |
|---|---|
A0-json |
no-catalog-not-enforced |
A1 |
schema-dump-catalog-not-enforced-gated |
A2 |
schema-dump-catalog-flat-enforced |
A2-enforced-only |
schema-prose-catalog-flat-enforced |
A2-strict |
schema-dump-catalog-flat-enforced-strict |
A4-blind |
no-catalog-enforced |
A4-enforced-only |
schema-prose-catalog-enforced |
schema-prose-catalog and schema-prose-full-catalog are the same arm at
two catalogue depths, which is a property of the run and not of the arm, so
the name is derived from the record's own enforcement block.
Comparability
corpus_hash and catalogue_hash place a record against the generation it
was measured on. Quantity records are not comparable across a change in
either: the catalogue rendering decides whether the prompt states the unit
enumeration the grammar enforces, and two generations of the schema module
differ in the case of 234 kinds' unit identifiers.
benchmark_sha reads local in records written before the runner was
committed, so those do not pin a code revision. Later ones do.
Reproducing
uv sync --extra agent --extra corpora
oold-bench fetch-corpus quantities --dest ./schemas
oold-bench grids
oold-bench run context-ladder --models unsloth/Qwen3.5-9B --schemas ./schemas
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