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"name": "p_arc_potarcin_tabular",
"primary_file": "p_arc_dataset.csv",
"encoding": "utf-8",
"format": "csv",
"quoting": "QUOTE_NONNUMERIC",
"notes": [
"Cells may exceed Python's default csv.field_size_limit (~128 KiB); use csv.field_size_limit(sys.maxsize).",
"Train/test grids match Test2/t<n>.json; stable_instances_50_json is json.loads(t<n>_samples_50.json) re-serialized as compact JSON (same data as on disk, no decorative whitespace).",
"generator_py and verifier_py match Test2/<subdir>/generator.py and verifier.py verbatim."
],
"columns": [
{
"name": "task_id",
"type": "string",
"description": "Task id from t1 through t50."
},
{
"name": "train_demonstrations_json",
"type": "json_string",
"description": "Compact JSON array of training pairs {input, output}; grids are List[List[int]]."
},
{
"name": "test_input_json",
"type": "json_string",
"description": "Compact JSON grid for test[0].input."
},
{
"name": "test_output_json",
"type": "json_string",
"description": "Compact JSON grid for test[0].output (published gold)."
},
{
"name": "stable_instances_50_json",
"type": "json_string",
"description": "Compact JSON object parsed from t<n>_samples_50.json (stable sample bundle; minimal separators, no pretty-print)."
},
{
"name": "generator_py",
"type": "string",
"description": "UTF-8 Python source for the task generator."
},
{
"name": "verifier_py",
"type": "string",
"description": "UTF-8 Python source for the task verifier."
}
]
}
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