Datasets:
File size: 3,203 Bytes
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"meta_info": {
"case_id": "MentalArithmetic_01.edf",
"bench_subset": "NeuroBench-Core",
"difficult": 1.5,
"original_dataset": "MentalArithmetic"
},
"agent_input": {
"data_path": "data/core/MentalArithmetic_01.edf",
"instruction": "Please select EEG channels from the raw signal, apply a 0.5-40Hz FIR bandpass filter, compute pairwise Pearson correlation coefficients between EEG channels, and then return the top 3 channel pairs sorted by coefficient from highest to lowest. Report only channel pairs in descending order."
},
"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 final Top-3 channel-pair sequence ranked by Pearson correlation coefficient from high to low.\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 key in JSON must be EXACTLY \"top3_pairs\".\n5. The value of \"top3_pairs\" must be an array of exactly 3 strings.\n6. Normalize EACH reported pair independently. First identify the two complete source channel labels; a referenced label such as F4-A1 is one complete channel label, and its hyphen must not be treated as the pair separator.\n7. For each source channel separately, uppercase it and remove one terminal reference suffix if present: -A1, -A2, -LE, -REF, -M1, -M2, or -AVG. Never output a reference electrode (A1/A2/LE/REF/M1/M2/AVG) as a pair member.\n8. Convert legacy aliases after removing the reference suffix: T3->T7, T4->T8, T5->P7, T6->P8.\n9. Sort the two normalized channel labels in ascending lexicographic order, then join them with exactly one hyphen using format \"CH1-CH2\" (uppercase, no spaces). If the report already uses a canonical pair such as F4-C4, normalize it to C4-F4. Each final label may contain only uppercase A-Z letters and digits; mixed-case forms such as Fp1 or Fp2 are forbidden and must become FP1 or FP2.\n10. Required examples: \"F4-A1 and C4-A1\" -> \"C4-F4\"; \"F4-C4\" -> \"C4-F4\"; \"T4-A1 and T3-A2\" -> \"T7-T8\"; \"Fp2 and Fp1\" -> \"FP1-FP2\".\n11. Preserve the three pairs in descending correlation order as reported. Do not sort the three-element array lexicographically.\n12. If any pair cannot be resolved into exactly two non-reference channels, return {\"top3_pairs\": null}; do not guess.\n\n### OUTPUT TEMPLATE\n{\"top3_pairs\": [\"CH1-CH2\", \"CH3-CH4\", \"CH5-CH6\"]}",
"metrics": [
{
"metric_id": "top3_corr_pairs_sequence",
"type": "sequence_match_check",
"target_key": "top3_pairs",
"weight": 100,
"params": {
"gt_value": [
"F4-FZ",
"FP1-FP2",
"F3-FP1"
],
"match_mode": "exact_order",
"top_k": 3
}
}
]
}
}
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