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.

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Your search for Benchmark 'book_advert_xml__true' with Search Hidden 'False' returned 90 results, showing page 1 of 9.
Result 1 of 90

Test T0837 at 2026-03-25

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

Configuration
Provideralibaba
Modelqwen3.5-35b-a3b
  
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
92.93 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: 39.2K IT + 442.2K OT = 481.4K TTCost: 0.010$ + 0.884$ = 0.894$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 2 of 90

Test T0863 at 2026-03-25

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

Configuration
Provideralibaba
Modelqwen3.5-122b-a10b
  
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
96.00 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: 39.2K IT + 442.9K OT = 482.1K TTCost: 0.016$ + 1.417$ = 1.433$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 3 of 90

Test T0876 at 2026-03-25

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

Configuration
Provideralibaba
Modelqwen3.5-397b-a17b
  
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
91.74 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: 39.2K IT + 444.5K OT = 483.8K TTCost: 0.024$ + 1.600$ = 1.624$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 4 of 90

Test T0752 at 2026-03-25

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

Configuration
Providerdeepseek
Modeldeepseek-chat
  
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
96.39 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: 39.4K IT + 33.8K OT = 73.2K TTCost: 0.011$ + 0.014$ = 0.025$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 5 of 90

Test T0889 at 2026-03-25

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

Configuration
Provideralibaba
Modelqwen3.5-flash-2026-02-23
  
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
83.62 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/a, n/a. Tokens: 39.2K IT + 459.8K OT = 499.1K TTCost: 0.004$ + 0.184$ = 0.188$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 6 of 90

Test T0850 at 2026-03-25

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

Configuration
Provideralibaba
Modelqwen3.5-27b
  
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
95.84 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: 39.2K IT + 413.5K OT = 452.7K TTCost: 0.012$ + 0.992$ = 1.004$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 7 of 90

Test T0764 at 2026-03-25

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

Configuration
Providerdeepseek
Modeldeepseek-reasoner
  
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
95.85 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: 39.4K IT + 230.2K OT = 269.6K TTCost: 0.011$ + 0.097$ = 0.108$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 8 of 90

Test T0824 at 2026-03-24

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

Configuration
Provideralibaba
Modelqwen3.5-plus
  
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
95.80 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: 39.2K IT + 432.7K OT = 472.0K TTCost: 0.016$ + 1.038$ = 1.054$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 9 of 90

Test T0728 at 2026-03-23

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

Configuration
Providerx-ai
Modelgrok-4.20-0309-reasoning
  
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
98.61 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: 40.4K IT + 26.7K OT = 67.0K TTCost: 0.081$ + 0.160$ = 0.241$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 10 of 90

Test T0703 at 2026-03-23

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

Configuration
Provideropenai
Modelgpt-5.3-codex
  
Temperature1.0
Dataclassnot set (=no auto-parsed result)
  
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
97.35 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: 27.9K IT + 29.7K OT = 57.7K TTCost: 0.049$ + 0.416$ = 0.465$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752