Datasets:
File size: 1,998 Bytes
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"meta_info": {
"case_id": "Q27",
"bench_subset": "NeuroBench-Core",
"difficult": 1.0,
"original_dataset": "Core_QA",
"references": "R6,R7"
},
"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: Which interpretation is a common pitfall when analyzing beta activity?\nA. Mistaking high-frequency frontotemporal EMG activity for cortical beta/gamma activity.\nB. Treating beta as a frequency band that is usually higher than alpha.\nC. Considering task context, medication, and muscle tone when interpreting beta.\nD. Reporting the beta-band boundaries and checking for high-frequency artifact contamination."
},
"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": "A"
}
}
]
}
} |