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epfl-dlab
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JSONSchemaBench

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Text Generation
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metadata
pretty_name: J
dataset_info:
  - config_name: Github_easy
    features:
      - name: json_schema
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      - name: unique_id
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configs:
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    data_files:
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        path: data/Github_ultra-*
      - split: JsonSchemaStore
        path: data/JsonSchemaStore-*
      - split: Glaiveai2K
        path: data/Glaiveai2K-*
license: mit
task_categories:
  - text-generation

JSONSchemaBench

Paper GitHub

JSONSchemaBench is a benchmark of real-world JSON schemas designed to evaluate structured output generation for Large Language Models (LLMs). It contains approximately 10,000 JSON schemas, capturing diverse constraints and complexities.

📌 Dataset Overview

  • Purpose: Evaluate the efficiency and coverage of structured output generation.
  • Sources: GitHub, Kubernetes, API specifications, curated collections.
  • Schemas: Categorized based on complexity and domain.

📊 Dataset Breakdown

Dataset Category Count
GlaiveAI-2K Function Call 1707
Github-Trivial Misc 444
Github-Easy Misc 1943
Snowplow Operational API 403
Github-Medium Misc 1976
Kubernetes Kubernetes API 1064
Washington Post Resource Access API 125
Github-Hard Misc 1240
JSONSchemaStore Misc 492
Github-Ultra Misc 164
Total 9558

📥 Loading the Dataset 

from datasets import load_dataset

dataset = load_dataset("epfl-dlab/JSONSchemaBench")
print(dataset)

🔍 Data Structure

Each dataset split contains:

  • "json_schema": The schema definition.
  • "unique_id": A unique identifier for the schema.

🚀 For more details, check out the paper.

📚 Citation 

@misc{geng2025jsonschemabench,
      title={Generating Structured Outputs from Language Models: Benchmark and Studies},
      author={Saibo Geng et al.},
      year={2025},
      eprint={2501.10868},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.10868}
}

License

This dataset is provided under the MIT License. Please ensure that you comply with the license terms when using or distributing this dataset.

Acknowledgements

We would like to thank the contributors and maintainers of the JSON schema projects and the open-source community for their invaluable work and support.