Datasets:
File size: 1,852 Bytes
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"meta_info": {
"case_id": "Q22",
"bench_subset": "NeuroBench-Core",
"difficult": 1.0,
"original_dataset": "Core_QA",
"references": "R21"
},
"agent_input": {
"data_path": "",
"instruction": "This is a standalone EEG/BCI knowledge multiple-choice question. No EEG data file is needed. Please answer by selecting exactly one option: A, B, C, or D.\n\nQuestion: What is the core idea of the REST reference method?\nA. Simply adding the left and right mastoid references.\nB. Keeping only the Cz channel.\nC. Replacing re-referencing with notch filtering.\nD. Estimating potentials relative to an approximately infinity reference."
},
"eval_config": {
"parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for multiple-choice EEG/BCI QA responses. Your sole task is to extract the final selected answer option.\n\n### TASK\nExtract the final selected option from the agent report.\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. DO NOT include Markdown code blocks.\n3. DO NOT include any conversational text, explanations, or units.\n4. The key must be EXACTLY \"selected_option\".\n5. The value must be one of \"A\", \"B\", \"C\", \"D\", or null.\n6. If multiple options are mentioned, extract only the final answer option.\n7. If the selected option is missing or unclear, return {\"selected_option\": null}.\n\n### OUTPUT TEMPLATE\n{\"selected_option\": <string|null>}",
"metrics": [
{
"metric_id": "qa_option_accuracy",
"type": "categorical_check",
"target_key": "selected_option",
"weight": 100,
"params": {
"gt_value": "D"
}
}
]
}
} |