RISE Humanities Data Benchmark, 0.5.0-pre1

Search Test Runs

 

A test run is a single execution of a benchmark test using a defined model configuration.
Each run represents how a particular large language model (LLM) — such as GPT-4, Claude-3, or Gemini — performed on a given task at a specific time, with specific settings.

A test run includes:

  • Prompt and role definition – what the model was asked to do and from what perspective (e.g. “as a historian”).
  • Model configuration – provider, model version, temperature, and other generation parameters.
  • Results – the model’s actual response and its evaluation (scores such as F1 or accuracy).
  • Usage and cost data – token counts and calculated API costs.
  • Metadata – information like the test date, benchmark name, and person who executed it.

Together, test runs make it possible to compare models, providers, and configurations across benchmarks in a transparent and reproducible way.

Search Results

Your search for Benchmark 'book_advert_xml__true' with Search Hidden 'False' returned 90 results, showing page 8 of 9.
Result 71 of 90

Test T0461 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Providergenai
Modelgemini-2.5-flash-lite-preview-09-2025
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
67.71 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 31.5K IT + 816.8K OT = 848.3K TTCost: 0.003$0.327$0.330$
Result 72 of 90

Test T0446 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideropenai
Modelgpt-4o-2024-08-06
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
95.66 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 33.8K IT + 27.4K OT = 61.2K TTCost: 0.000$0.000$0.000$
Result 73 of 90

Test T0480 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideropenai
Modelqwen/qwen3-vl-8b-instruct
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
54.90 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 37.2K IT + 27.4K OT = 64.6K TTCost: 0.000$0.000$0.006$
Result 74 of 90

Test T0456 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Providergenai
Modelgemini-2.0-flash
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
93.23 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 35.4K IT + 30.1K OT = 65.6K TTCost: 0.004$0.012$0.016$
Result 75 of 90

Test T0455 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideropenai
Modelo3
  
Temperature1.0
DataclassCorrectedAdvert
  
Normalized Score0.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.00 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 0 IT + 0 OT = 0 TTCost: 0.000$0.000$0.000$
Result 76 of 90

Test T0466 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideranthropic
Modelclaude-sonnet-4-20250514
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
96.99 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 60.4K IT + 35.2K OT = 95.7K TTCost: 0.181$0.528$0.710$
Result 77 of 90

Test T0467 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideranthropic
Modelclaude-opus-4-1-20250805
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
96.62 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 60.4K IT + 35.8K OT = 96.2K TTCost: 0.907$2.685$3.592$
Result 78 of 90

Test T0479 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideropenai
Modelqwen/qwen3-vl-30b-a3b-instruct
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
96.38 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 34.5K IT + 37.8K OT = 72.3K TTCost: 0.000$0.000$0.000$
Result 79 of 90

Test T0476 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Provideropenai
ModelGLM-4.5V-FP8
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score0.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.00 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 0 IT + 0 OT = 0 TTCost: 0.000$0.000$0.000$
Result 80 of 90

Test T0470 at 2025-12-08

{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}

Configuration
Providermistral
Modelmistral-medium-2508
  
Temperature0.0
DataclassCorrectedAdvert
  
Normalized Score100.00 %
Test timeunknown seconds
Prompt

Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.

Results

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
83.67 n/a n/a n/a n/a n/a n/a n/a n/a
      Micro Precision Micro Recall Instances TP FP FN
Costs / Pricing
Pricing Date: n/an/aTokens: 40.3K IT + 31.8K OT = 72.1K TTCost: 0.016$0.064$0.080$