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test: add LLM retrieval accuracy tests
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95
benchmarks/results/accuracy/summary.json
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95
benchmarks/results/accuracy/summary.json
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{
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"formatResults": [
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{
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"format": "toon",
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"accuracy": 0.7389937106918238,
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"totalTokens": 4678,
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"avgInputTokens": 4675,
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"avgLatency": 1424,
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"correctCount": 235,
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"totalCount": 318
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},
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{
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"format": "json",
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"accuracy": 0.7358490566037735,
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"totalTokens": 8713,
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"avgInputTokens": 9177,
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"avgLatency": 1678,
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"correctCount": 234,
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"totalCount": 318
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},
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{
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"format": "markdown-kv",
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"accuracy": 0.7358490566037735,
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"totalTokens": 8649,
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"avgInputTokens": 8242,
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"avgLatency": 1724,
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"correctCount": 234,
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"totalCount": 318
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},
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{
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"format": "csv",
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"accuracy": 0.7232704402515723,
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"totalTokens": 4745,
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"avgInputTokens": 4878,
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"avgLatency": 1573,
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"correctCount": 230,
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"totalCount": 318
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},
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{
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"format": "yaml",
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"accuracy": 0.7169811320754716,
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"totalTokens": 7091,
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"avgInputTokens": 7136,
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"avgLatency": 1602,
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"correctCount": 228,
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"totalCount": 318
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}
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],
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"questions": 159,
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"models": [
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"gpt-4o-mini",
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"claude-haiku-4-5"
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],
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"datasets": [
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{
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"name": "tabular",
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"description": "Uniform employee records (TOON optimal format)"
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},
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{
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"name": "nested",
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"description": "E-commerce orders with nested structures"
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},
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{
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"name": "analytics",
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"description": "Time-series analytics data"
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},
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{
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"name": "github",
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"description": "Popular GitHub repositories"
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}
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],
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"tokenCounts": {
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"json-tabular": 6347,
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"json-nested": 9694,
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"json-analytics": 3665,
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"json-github": 15145,
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"toon-tabular": 2483,
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"toon-nested": 5967,
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"toon-analytics": 1515,
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"toon-github": 8745,
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"csv-tabular": 2337,
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"csv-nested": 6735,
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"csv-analytics": 1393,
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"csv-github": 8513,
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"markdown-kv-tabular": 6270,
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"markdown-kv-nested": 9110,
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"markdown-kv-analytics": 3779,
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"markdown-kv-github": 15436,
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"yaml-tabular": 4969,
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"yaml-nested": 7328,
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"yaml-analytics": 2938,
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"yaml-github": 13129
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},
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"timestamp": "2025-10-27T10:46:35.127Z"
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}
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