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 'magazine_pages__true' with Search Hidden 'False' returned 52 results, showing page 6 of 6.
Result 51 of 52

Test T0711 at 2026-03-21

{'century': [20], 'document-type': ['newspaper-page'], 'language': ['en'], 'layout': ['prose', 'columns'], 'script': ['latin'], 'task': ['document-understanding'], 'writing': ['printed']}

Configuration
Providergenai
Modelgemini-3.1-pro-preview
  
Temperature0.0
DataclassMagazinePage
  
Normalized Score0.00 %
Test timeunknown seconds
Prompt 

Extract all advertisements and return their bounding boxes.
The original size of the page is {width} x {height} pixels.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 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: 52.3K IT + 3.4K OT = 55.7K TTCost: 0.105$ + 0.041$ = 0.145$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752
Result 52 of 52

Test T0714 at 2026-03-21

{'century': [20], 'document-type': ['newspaper-page'], 'language': ['en'], 'layout': ['prose', 'columns'], 'script': ['latin'], 'task': ['document-understanding'], 'writing': ['printed']}

Configuration
Provideropenai
Modelgpt-5.4-2026-03-05
  
Temperature1.0
DataclassMagazinePage
  
Normalized Score70.90 %
Test timeunknown seconds
Prompt 

Extract all advertisements and return their bounding boxes.
The original size of the page is {width} x {height} pixels.

Results 

no valid result

Scoring
Fuzzy Score F1 micro / macro Micro precision/recall Tue/False Positives
n/a 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: 136.7K IT + 2.2K OT = 138.9K TTCost: 0.342$ + 0.034$ = 0.375$
Cite: Hindermann, Marti, Alberto, et al., (2025). RISE-UNIBAS/humanities_data_benchmark, 10.5281/zenodo.16941752