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 7 of 9.
Result 61 of 90

Test T0459 at 2025-12-08

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

Configuration
Providergenai
Modelgemini-2.5-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
90.78 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 + 74.8K OT = 106.3K TTCost: 0.009$0.187$0.196$
Result 62 of 90

Test T0471 at 2025-12-08

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

Configuration
Providermistral
Modelmistral-medium-2505
  
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
84.58 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 + 32.3K OT = 72.6K TTCost: 0.016$0.065$0.081$
Result 63 of 90

Test T0469 at 2025-12-08

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

Configuration
Providermistral
Modelpixtral-large-2411
  
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
86.42 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: 44.8K IT + 46.4K OT = 91.2K TTCost: 0.090$0.278$0.368$
Result 64 of 90

Test T0453 at 2025-12-08

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

Configuration
Provideropenai
Modelgpt-5-nano-2025-08-07
  
Temperature1.0
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
94.18 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: 33.6K IT + 600.3K OT = 633.9K TTCost: 0.002$0.240$0.242$
Result 65 of 90

Test T0452 at 2025-12-08

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

Configuration
Provideropenai
Modelgpt-5-mini-2025-08-07
  
Temperature1.0
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
91.12 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: 33.7K IT + 176.7K OT = 210.4K TTCost: 0.008$0.353$0.362$
Result 66 of 90

Test T0454 at 2025-12-08

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

Configuration
Provideropenai
Modelgpt-5.1-2025-11-13
  
Temperature1.0
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
95.68 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: 33.6K IT + 36.9K OT = 70.5K TTCost: 0.000$0.000$0.000$
Result 67 of 90

Test T0478 at 2025-12-08

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

Configuration
Provideropenai
Modelmeta-llama/llama-4-maverick
  
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
67.18 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: 29.7K IT + 24.8K OT = 54.5K TTCost: 0.000$0.000$0.003$
Result 68 of 90

Test T0449 at 2025-12-08

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

Configuration
Provideropenai
Modelgpt-4.1-mini-2025-04-14
  
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
90.13 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: 33.9K IT + 61.1K OT = 95.0K TTCost: 0.000$0.000$0.000$
Result 69 of 90

Test T0481 at 2025-12-08

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

Configuration
Provideropenai
Modelx-ai/grok-4
  
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
95.09 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: 68.1K IT + 452.5K OT = 520.7K TTCost: 0.000$0.000$0.143$
Result 70 of 90

Test T0477 at 2025-12-08

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

Configuration
Provideropenai
Modelqwen/qwen3-vl-8b-thinking
  
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
1.91 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: 21.0K IT + 23.2K OT = 44.2K TTCost: 0.000$0.000$0.000$