Datasets:
File size: 4,754 Bytes
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"meta_info": {
"case_id": "BCIC2020-3_03.edf",
"bench_subset": "NeuroBench-Core",
"difficult": 1.0,
"original_dataset": "BCIC2020-3"
},
"agent_input": {
"data_path": "data/core/BCIC2020-3_03.edf",
"instruction": "Please keep only the real EEG channels from the raw signal, use the first 120 seconds, re-reference the EEG data to average reference, and save the processed EEG EDF file to the file_check directory with the filename BCIC2020-3_03_case15_processed.edf."
},
"eval_config": {
"parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for neurophysiological data. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract the saved EEG file path 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 or explanations.\n4. The JSON key must be EXACTLY \"file_path\".\n5. The value must be a string file path or null.\n6. If the report does not clearly provide a saved file path, return null.\n\n### OUTPUT TEMPLATE\n{\"file_path\": \"file_check/example_processed.edf\"}",
"metrics": [
{
"metric_id": "save_avgref_real_eeg_edf_status",
"type": "file_status_check",
"target_key": "file_path",
"weight": 100,
"params": {
"match_mode": "eeg_file_match",
"validator_config": {
"file_name": {
"value": "BCIC2020-3_03_case15_processed.edf"
},
"duration_sec": {
"value": 120.0,
"weight": 33
},
"channel_names": {
"value": [
"Fp1",
"Fp2",
"F7",
"F3",
"Fz",
"F4",
"F8",
"FC5",
"FC1",
"FC2",
"FC6",
"T7",
"C3",
"Cz",
"C4",
"T8",
"TP9",
"CP5",
"CP1",
"CP2",
"CP6",
"TP10",
"P7",
"P3",
"Pz",
"P4",
"P8",
"PO9",
"O1",
"Oz",
"O2",
"PO10",
"AF7",
"AF3",
"AF4",
"AF8",
"F5",
"F1",
"F2",
"F6",
"FT9",
"FT7",
"FC3",
"FC4",
"FT8",
"FT10",
"C5",
"C1",
"C2",
"C6",
"TP7",
"CP3",
"CPz",
"CP4",
"TP8",
"P5",
"P1",
"P2",
"P6",
"PO7",
"PO3",
"POz",
"PO4",
"PO8"
],
"weight": 34
},
"reference_mode": {
"value": "average",
"weight": 33
}
}
}
}
]
}
} |