ALARB: Arabic Legal Argument Reasoning Benchmark

ALARB includes a dataset of structured legal cases in Arabic. Each case lists facts from the plaintiff and defendant, an explicit step-by-step chain of the court's argument reasoning, and links to applicable statutes. The dataset was created by THIQAH-RD and was last updated on the platform in October 2025.

Use Cases

• Train models for legal argument generation based on structured case facts.
• Benchmark natural language inference systems on Arabic legal reasoning chains.
• Analyze the relationship between case facts, statutory articles, and court verdicts.
• Develop tools for legal case summarization using the explicit reasoning steps.

Strengths

• Dataset provides explicit step-by-step reasoning chains for court decisions.
• Cases are linked to individual articles of applicable statutes and regulations.
• Includes structured facts from both plaintiff and defendant perspectives.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Freshness should be verified as the last update was 2025-10-15.

Provenance

Source

THIQAH-RD

Freshness

Last updated 2025-10-15 16:23:32.