sleep_assessment/cases/case01/case01_02.json

{
    "meta_info": {
        "case_id": "ISRUC_02.edf",
        "bench_subset": "NeuroBench-Sleep",
        "difficult": 1,
        "original_dataset": "ISRUC"
    },
    "agent_input": {
        "instruction": "Please use the provided sleep-stage label file to calculate the Sleep Onset Latency (SOL) for the provided sleep EEG/PSG recording. SOL is defined as the time in minutes from the first scored 30-second epoch to the first sleep epoch (N1, N2, N3, or REM). Please clearly state the final SOL value in minutes in your response.",
        "label_path": "data/sleep/ISRUC_02.npy"
    },
    "eval_config": {
        "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep medicine reports. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract the Sleep Onset Latency (SOL) value in minutes from the agent's report. SOL is defined in this benchmark as the time from the first scored 30-second epoch to the first sleep epoch.\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, explanations, or units.\n4. The key in the JSON must be EXACTLY \"sleep_onset_latency_min\".\n5. The value must be a FLOAT in minutes.\n6. If the value is missing or cannot be found, return {\"sleep_onset_latency_min\": null}.\n\n### OUTPUT TEMPLATE\n{\"sleep_onset_latency_min\": <float>}",
        "metrics": [
            {
                "metric_id": "sleep_onset_latency_accuracy",
                "type": "numeric_check",
                "target_key": "sleep_onset_latency_min",
                "weight": 100,
                "params": {
                    "gt_value": 55.0,
                    "tolerance": 2.0
                }
            }
        ]
    }
}