croissant: add rai:hasSyntheticData, absolute HF contentUrls, JSONL column extracts (all 4 NeurIPS checker checks pass)
Browse files- croissant.json +12 -11
croissant.json
CHANGED
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@@ -77,6 +77,7 @@
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| 77 |
"rai:dataLimitations": "Not intended as a deployment decision tool for safety-critical domains without additional validation. Template-generated questions do not fully capture naturalistic queries. Retrievability scores and failure buckets are heuristic and lack human validation; they should be treated as exploratory. API-based model results may vary across calls due to provider-side updates.",
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"rai:personalSensitiveInformation": "None. All data are synthetic or from public datasets with no personal or sensitive information. SciTabAlign contains scientific paper tables; ETT contains electricity transformer temperature measurements; NetworkX graphs are classic social-network datasets without personal identifiers.",
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"rai:dataUseCases": "Primary: benchmarking MLLM visualization-format dependence; secondary: representation-invariance research, evaluation-protocol research, diagnostic analysis of structured-data reasoning.",
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"keywords": [
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"multimodal",
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"benchmark",
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@@ -91,7 +92,7 @@
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"@id": "base-items-file",
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"name": "base_items.jsonl",
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"description": "Synthetic-only single-modality items: 1,500 questions (500 tabular + 500 time-series + 500 graph) from programmatically generated data.",
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"contentUrl": "benchmark/base_items.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "5d77094f209cb6e4d2fc2cbcd87da1f5dc55679b606f28798ddd26e0d9bc7e5b"
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},
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@@ -100,7 +101,7 @@
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"@id": "mixed-items-file",
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"name": "mixed_items.jsonl",
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"description": "Cross-modal composite evaluation items (600 items) requiring reasoning across two data modalities simultaneously (tabular+timeseries, tabular+graph, timeseries+graph).",
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"contentUrl": "benchmark/mixed_items.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "06f022e16dda6f35e8dbb01e1c8dd73ad6b981b399a4c7606b1943da78313d91"
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},
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@@ -109,7 +110,7 @@
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"@id": "realworld-test-file",
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"name": "realworld_test.jsonl",
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"description": "Full benchmark (3,795 items): superset containing all 1,500 synthetic items plus 2,295 real-world items (1,265 SciTabAlign tabular + 870 ETT time-series + 160 NetworkX graph). This is the primary evaluation file. Use the source field to filter by provenance.",
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"contentUrl": "benchmark/realworld_test.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "6ef2baf69daefac216200fbcc87df7087bb88e6d987390f64ce24364a2138779"
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}
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@@ -132,7 +133,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -147,7 +148,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -162,7 +163,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -177,7 +178,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -192,7 +193,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -207,7 +208,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -222,7 +223,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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"
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}
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}
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},
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@@ -237,7 +238,7 @@
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"@id": "base-items-file"
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},
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"extract": {
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-
"
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}
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}
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}
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"rai:dataLimitations": "Not intended as a deployment decision tool for safety-critical domains without additional validation. Template-generated questions do not fully capture naturalistic queries. Retrievability scores and failure buckets are heuristic and lack human validation; they should be treated as exploratory. API-based model results may vary across calls due to provider-side updates.",
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"rai:personalSensitiveInformation": "None. All data are synthetic or from public datasets with no personal or sensitive information. SciTabAlign contains scientific paper tables; ETT contains electricity transformer temperature measurements; NetworkX graphs are classic social-network datasets without personal identifiers.",
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"rai:dataUseCases": "Primary: benchmarking MLLM visualization-format dependence; secondary: representation-invariance research, evaluation-protocol research, diagnostic analysis of structured-data reasoning.",
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+
"rai:hasSyntheticData": true,
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"keywords": [
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"multimodal",
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"benchmark",
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"@id": "base-items-file",
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"name": "base_items.jsonl",
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"description": "Synthetic-only single-modality items: 1,500 questions (500 tabular + 500 time-series + 500 graph) from programmatically generated data.",
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"contentUrl": "https://huggingface.co/datasets/EvalData/StructViz-Bench/resolve/main/benchmark/base_items.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "5d77094f209cb6e4d2fc2cbcd87da1f5dc55679b606f28798ddd26e0d9bc7e5b"
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},
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"@id": "mixed-items-file",
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"name": "mixed_items.jsonl",
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"description": "Cross-modal composite evaluation items (600 items) requiring reasoning across two data modalities simultaneously (tabular+timeseries, tabular+graph, timeseries+graph).",
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"contentUrl": "https://huggingface.co/datasets/EvalData/StructViz-Bench/resolve/main/benchmark/mixed_items.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "06f022e16dda6f35e8dbb01e1c8dd73ad6b981b399a4c7606b1943da78313d91"
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},
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"@id": "realworld-test-file",
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"name": "realworld_test.jsonl",
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"description": "Full benchmark (3,795 items): superset containing all 1,500 synthetic items plus 2,295 real-world items (1,265 SciTabAlign tabular + 870 ETT time-series + 160 NetworkX graph). This is the primary evaluation file. Use the source field to filter by provenance.",
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"contentUrl": "https://huggingface.co/datasets/EvalData/StructViz-Bench/resolve/main/benchmark/realworld_test.jsonl",
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"encodingFormat": "application/jsonlines",
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"sha256": "6ef2baf69daefac216200fbcc87df7087bb88e6d987390f64ce24364a2138779"
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}
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"@id": "base-items-file"
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},
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"extract": {
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"column": "question_id"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "question"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "answer"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "modality"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "source"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "viz_methods"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "difficulty"
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}
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}
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},
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"@id": "base-items-file"
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},
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"extract": {
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"column": "task"
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}
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}
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}
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