RISE Humanities Data Benchmark, 0.5.3-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.

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Your search for Benchmark 'book_advert_xml__true' with Search Hidden 'False' returned 97 results, showing page 10 of 10.
Result 91 of 97

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/a, n/a. Tokens: 33.9K IT + 61.1K OT = 95.0K TTCost: 0.000$ + 0.000$ = 0.000$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 92 of 97

Test T0477 at 2025-12-08

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

Configuration
Provideropenrouter
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/a, n/a. Tokens: 21.0K IT + 23.2K OT = 44.2K TTCost: 0.000$ + 0.000$ = 0.000$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 93 of 97

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/a, n/a. Tokens: 0 IT + 0 OT = 0 TTCost: 0.000$ + 0.000$ = 0.000$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 94 of 97

Test T0479 at 2025-12-08

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

Configuration
Provideropenrouter
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/a, n/a. Tokens: 34.5K IT + 37.8K OT = 72.3K TTCost: 0.000$ + 0.000$ = 0.000$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 95 of 97

Test T0450 at 2025-12-08

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

Configuration
Provideropenai
Modelgpt-4.1-nano-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
93.35 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/a, n/a. Tokens: 33.8K IT + 25.4K OT = 59.1K TTCost: 0.000$ + 0.000$ = 0.000$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 96 of 97

Test T0458 at 2025-12-08

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

Configuration
Providergenai
Modelgemini-2.5-pro
  
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
91.54 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/a, n/a. Tokens: 31.5K IT + 28.6K OT = 60.1K TTCost: 0.039$ + 0.286$ = 0.325$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 97 of 97

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/a, n/a. Tokens: 31.5K IT + 74.8K OT = 106.3K TTCost: 0.009$ + 0.187$ = 0.196$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752