Datasets › AppealCase

AppealCase

Introduced by YuTing Huang et al. in AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios22 May 2025 archive 2025-07-28

The AppealCase dataset is the first large-scale resource specifically designed to support LegalAI research in appellate judgment scenarios. While prior work in LegalAI has focused heavily on one-shot trials, the appellate procedure—critical to ensuring fairness and correcting judicial errors—remains largely underexplored.

To bridge this gap, we construct 10,000 pairs of matched first-instance and second-instance civil cases from China Judgments Online, covering 91 causes of action. We also design a structured annotation schema and define new tasks tailored to the appellate context.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY-NC 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • AppealCase

1 variant name, as the archive lists them.

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