| { |
| "meta_info": { |
| "case_id": "ISRUC_02.edf", |
| "bench_subset": "NeuroBench-Sleep", |
| "difficult": 1, |
| "original_dataset": "ISRUC" |
| }, |
| "agent_input": { |
| "data_path": "data/sleep/ISRUC_02.edf", |
| "instruction": "Please inspect the provided raw sleep EEG/PSG file. Report the total number of channels in the file, and list all EEG channels that can be used for sleep analysis. Use the original channel names exactly as they appear in the raw file. Do not include EOG, EMG, ECG, respiratory, SpO2/SaO2, light, position, or other auxiliary channels in the EEG channel list." |
| }, |
| "eval_config": { |
| "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep EEG/PSG reports. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract two outputs from the agent report:\n1) the total number of channels in the raw file\n2) the list of all EEG channels using original raw-file channel names\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. DO NOT include Markdown code blocks.\n3. DO NOT include conversational text or explanations.\n4. The keys must be EXACTLY \"channel_count\" and \"eeg_channels\".\n5. \"channel_count\" must be an INTEGER or null.\n6. \"eeg_channels\" must be a JSON array of strings or null.\n7. Preserve original EEG channel names exactly as written in the raw file.\n8. Do NOT normalize references, casing, spacing, parentheses, hyphens, or symbols.\n9. Do NOT include EOG, EMG, ECG, respiratory, SpO2/SaO2, light, position, or auxiliary channels in \"eeg_channels\".\n10. For SHHS1 reports, only \"EEG(sec)\" and \"EEG\" count as EEG channels; \"THOR RES\", \"POSITION\", and \"OX stat\" are not EEG channels.\n11. Remove duplicate EEG channel names if the report repeats them.\n12. If one value is missing or unclear, return null for that value.\n\n### OUTPUT TEMPLATE\n{\"channel_count\": <integer|null>, \"eeg_channels\": <array|null>}", |
| "metrics": [ |
| { |
| "metric_id": "channel_count_accuracy", |
| "type": "numeric_check", |
| "target_key": "channel_count", |
| "weight": 30, |
| "params": { |
| "gt_value": 19, |
| "tolerance": 0.1 |
| } |
| }, |
| { |
| "metric_id": "eeg_channel_set_match", |
| "type": "set_match_check", |
| "target_key": "eeg_channels", |
| "weight": 70, |
| "params": { |
| "gt_value": [ |
| "F3-A2", |
| "C3-A2", |
| "O1-A2", |
| "F4-A1", |
| "C4-A1", |
| "O2-A1" |
| ], |
| "match_mode": "exact" |
| } |
| } |
| ] |
| } |
| } |
|
|
