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 'bibliographic_data__true' with Search Hidden 'False' returned 115 results, showing page 9 of 12.
Result 81 of 115

Test T0033 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providergenai
Modelgemini-2.0-flash-lite
  
Temperature0.0
DataclassDocument
  
Normalized Score39.15 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.39 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: 6 months ago, 2025-09-30. Tokens: 10.1K IT + 15.7K OT = 25.8K TTCost: 0.001$ + 0.005$ = 0.005$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 82 of 115

Test T0129 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Provideropenai
Modelgpt-5
  
Temperature0.0
DataclassDocument
  
Normalized Score67.33 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.67 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: 6 months ago, 2025-09-30. Tokens: 6.5K IT + 33.2K OT = 39.7K TTCost: 0.008$ + 0.332$ = 0.340$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 83 of 115

Test T0133 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Provideropenai
Modelo3
  
Temperature0.0
DataclassDocument
  
Normalized Score67.37 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.67 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: 6 months ago, 2025-09-30. Tokens: 6.7K IT + 22.8K OT = 29.5K TTCost: 0.013$ + 0.182$ = 0.196$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 84 of 115

Test T0008 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providergenai
Modelgemini-2.0-flash
  
Temperature0.0
DataclassDocument
  
Normalized Score60.40 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.60 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: 6 months ago, 2025-09-30. Tokens: 10.1K IT + 10.6K OT = 20.7K TTCost: 0.001$ + 0.004$ = 0.005$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 85 of 115

Test T0035 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providermistral
Modelpixtral-large-latest
  
Temperature0.0
DataclassDocument
  
Normalized Score50.84 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.51 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: 6 months ago, 2025-09-30. Tokens: 18.6K IT + 11.8K OT = 30.4K TTCost: 0.037$ + 0.071$ = 0.108$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 86 of 115

Test T0128 at 2025-09-30

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providergenai
Modelgemini-2.5-pro
  
Temperature0.0
DataclassDocument
  
Normalized Score66.38 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.66 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: 6 months ago, 2025-09-30. Tokens: 1.7K IT + 10.1K OT = 11.8K TTCost: 0.002$ + 0.101$ = 0.103$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 87 of 115

Test T0170 at 2025-09-26

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providermistral
Modelmistral-medium-2505
  
Temperature0.0
DataclassDocument
  
Normalized Score61.24 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.61 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: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 88 of 115

Test T0169 at 2025-09-26

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providermistral
Modelmistral-medium-2508
  
Temperature0.0
DataclassDocument
  
Normalized Score58.84 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.59 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: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 89 of 115

Test T0035 at 2025-09-25

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Providermistral
Modelpixtral-large-latest
  
Temperature0.0
DataclassDocument
  
Normalized Score39.42 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.39 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: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 90 of 115

Test T0107 at 2025-09-24

{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}

Configuration
Provideranthropic
Modelclaude-sonnet-4-20250514
  
Temperature0.0
DataclassDocument
  
Normalized Score64.02 %
Test timeunknown seconds
Prompt
Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
0.64 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: n/a IT + n/a OT = n/a TTCost: n/a$ + n/a$ = n/a$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752