Datasets:
| { | |
| "meta_info": { | |
| "case_id": "ISRUC_01.edf", | |
| "bench_subset": "NeuroBench-Core", | |
| "difficult": 1.0, | |
| "original_dataset": "ISRUC" | |
| }, | |
| "agent_input": { | |
| "data_path": "data/core/ISRUC_01.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 ISRUC_01_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": "ISRUC_01_case15_processed.edf" | |
| }, | |
| "duration_sec": { | |
| "value": 120.0, | |
| "weight": 33 | |
| }, | |
| "channel_names": { | |
| "value": [ | |
| "F3-A2", | |
| "C3-A2", | |
| "O1-A2", | |
| "F4-A1", | |
| "C4-A1", | |
| "O2-A1" | |
| ], | |
| "weight": 34 | |
| }, | |
| "reference_mode": { | |
| "value": "average", | |
| "weight": 33 | |
| } | |
| } | |
| } | |
| } | |
| ] | |
| } | |
| } |