Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
model: string
timestamp: string
repeats: int64
runs: list<item: struct<run: int64, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: (... 2384 chars omitted)
child 0, item: struct<run: int64, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: int64, 15: (... 2372 chars omitted)
child 0, run: int64
child 1, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: int64, 15: int64, 16: int64, 21: int64 (... 998 chars omitted)
child 0, 1: int64
child 1, 2: int64
child 2, 4: int64
child 3, 9: int64
child 4, 13: int64
child 5, 14: int64
child 6, 15: int64
child 7, 16: int64
child 8, 21: int64
child 9, 24: int64
child 10, 25: int64
child 11, 26: int64
child 12, 28: int64
child 13, 29: int64
child 14, 30: int64
child 15, 31: int64
child 16, 32: int64
child 17, 33: int64
child 18, 35: int64
child 19, 36: int64
child 20, 49: int64
child 21, 52: int64
child 22, 53: int64
child 23, 54: int64
child 24, 57: int64
child 25, 58: int64
child 26, 59: int64
child 27, 60: int64
child 28, 61: int64
child 29, 63: int64
child 30, 65: int64
child 31, 66: int64
child 32, 67: int64
child 33, 68: int
...
over (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 1, scores_std: struct<society: double, politics: double, economics: double, state: double, diplomacy: double, gover (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 2, scores_runs: list<item: struct<society: double, politics: double, economics: double, state: double, diplomacy: do (... 64 chars omitted)
child 0, item: struct<society: double, politics: double, economics: double, state: double, diplomacy: double, gover (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 3, repeats: int64
child 4, forced_choice: bool
child 5, failure_count: int64
child 6, failures: list<item: null>
child 0, item: null
child 7, failures_per_run: list<item: int64>
child 0, item: int64
to
{'qwen3-coder': {'scores': {'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}, 'scores_std': {'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}, 'scores_runs': List({'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}), 'repeats': Value('int64'), 'forced_choice': Value('bool'), 'failure_count': Value('int64'), 'failures': List(Value('null')), 'failures_per_run': List(Value('int64'))}}
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
model: string
timestamp: string
repeats: int64
runs: list<item: struct<run: int64, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: (... 2384 chars omitted)
child 0, item: struct<run: int64, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: int64, 15: (... 2372 chars omitted)
child 0, run: int64
child 1, answers: struct<1: int64, 2: int64, 4: int64, 9: int64, 13: int64, 14: int64, 15: int64, 16: int64, 21: int64 (... 998 chars omitted)
child 0, 1: int64
child 1, 2: int64
child 2, 4: int64
child 3, 9: int64
child 4, 13: int64
child 5, 14: int64
child 6, 15: int64
child 7, 16: int64
child 8, 21: int64
child 9, 24: int64
child 10, 25: int64
child 11, 26: int64
child 12, 28: int64
child 13, 29: int64
child 14, 30: int64
child 15, 31: int64
child 16, 32: int64
child 17, 33: int64
child 18, 35: int64
child 19, 36: int64
child 20, 49: int64
child 21, 52: int64
child 22, 53: int64
child 23, 54: int64
child 24, 57: int64
child 25, 58: int64
child 26, 59: int64
child 27, 60: int64
child 28, 61: int64
child 29, 63: int64
child 30, 65: int64
child 31, 66: int64
child 32, 67: int64
child 33, 68: int
...
over (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 1, scores_std: struct<society: double, politics: double, economics: double, state: double, diplomacy: double, gover (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 2, scores_runs: list<item: struct<society: double, politics: double, economics: double, state: double, diplomacy: do (... 64 chars omitted)
child 0, item: struct<society: double, politics: double, economics: double, state: double, diplomacy: double, gover (... 52 chars omitted)
child 0, society: double
child 1, politics: double
child 2, economics: double
child 3, state: double
child 4, diplomacy: double
child 5, government: double
child 6, technology: double
child 7, religion: double
child 3, repeats: int64
child 4, forced_choice: bool
child 5, failure_count: int64
child 6, failures: list<item: null>
child 0, item: null
child 7, failures_per_run: list<item: int64>
child 0, item: int64
to
{'qwen3-coder': {'scores': {'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}, 'scores_std': {'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}, 'scores_runs': List({'society': Value('float64'), 'politics': Value('float64'), 'economics': Value('float64'), 'state': Value('float64'), 'diplomacy': Value('float64'), 'government': Value('float64'), 'technology': Value('float64'), 'religion': Value('float64')}), 'repeats': Value('int64'), 'forced_choice': Value('bool'), 'failure_count': Value('int64'), 'failures': List(Value('null')), 'failures_per_run': List(Value('int64'))}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
About
This benchmark examines how AI models behave politically. The questions come from the 8D Political Compass (github.com/haroldini/8D-PolComp). Each model completed 5 runs and received only a neutral instruction on how to answer: with a number from -2 to 2, with the meaning of each number explained. Reasoning models were tested with their standard reasoning settings.
How the models were run
The analysis was performed through the Mammouth AI API, which uses OpenRouter in the background. The open Chinese models were run by Fireworks AI.
- Downloads last month
- 357