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sdc-prompts-medium-v1
Prompts for Medium tier
Dataset Info
- Rows: 160
- Columns: 4
Columns
| Column | Type | Description |
|---|---|---|
| problem_id | Value('string') | Problem identifier (M01-M20) |
| language | Value('string') | Target programming language |
| tiobe_rank | Value('int64') | TIOBE index rank |
| prompt | Value('string') | Full prompt text sent to GPT-5.2 |
Generation Parameters
{
"script_name": "run_medium_zero_shot.py",
"model": "gpt-5-2",
"description": "Prompts for Medium tier",
"tier": "medium",
"hyperparameters": {
"temperature": 0.7,
"max_tokens": "model_maximum"
},
"input_datasets": [
"Lossfunk/Esolang-Bench"
]
}
Experiment Documentation
For complete experiment details, see https://github.com/Zayne-sprague/SC-Research-Notes/tree/main/experiments/semantic-distance-coding
Usage
from datasets import load_dataset
dataset = load_dataset("reasoning-degeneration-dev/sdc-prompts-medium-v1", split="train")
print(f"Loaded {len(dataset)} rows")
This dataset is tracked in reasoning-degeneration-dev/PROJECT-MANIFEST
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