Saudi ESB Dataset

This dataset contains 10,000 synthetic samples for training and evaluating AI systems
for Saudi Arabia's End-of-Service Benefits (ESB) calculation under Saudi Labour Law
(Royal Decree M/51, 2005; amended 2015). The dataset systematically models real-world
legal consultation complexities absent from existing legal AI benchmarks.

KEY FEATURES:
- 10,000 query-response pairs (8,000 train / 1,000 validation / 1,000 test)
- Six complexity tiers: Standard cases (60%), Incomplete information (15%), Conflicting
evidence (10%), Legal interpretation (5%), Multi-step reasoning (5%), Adversarial (5%)
- Explicit uncertainty modeling with confidence scores (0-1 scale)
- Coverage: 16 Saudi Labour Law articles (74-88, 137-138, 234), 35 termination scenarios
- 2,000 multi-turn conversations (20% of dataset)
- Empirically grounded: Distributions derived from 47,382 real ESB cases (Saudi Ministry
of Human Resources, 2019-2023), 3,847 labor court disputes, and HR consultant interviews (n=23)

DATA STRUCTURE:
Each sample includes:
- Query: Natural language employee profile with service years, salary, termination type
- Ground truth: ESB amount (SAR), applicable legal articles, calculation steps
- Confidence score: 0-1 scale reflecting query ambiguity
- Complexity tier: 1-6 classification
- Metadata: Employee demographics, termination scenario, multi-turn conversation flag

VALIDATION:
- 97.3% pass rate on 12 automated validation checks
- Expert validation by Saudi labor law professionals
- Stratified sampling ensures representativeness across termination scenarios

APPLICATIONS:
- Training legal AI systems for ESB calculation
- Benchmarking uncertainty quantification methods
- Evaluating robustness to incomplete information and adversarial inputs
- Research on parameter-efficient fine-tuning and retrieval-augmented generation

LIMITATIONS:
- Synthetic data (not actual legal cases) due to privacy constraints
- Focused on ESB calculation only (16 of 245 Saudi Labour Law articles)
- Requires domain expertise for interpretation and application

LICENSE: CC BY 4.0 (recommended - allows reuse with attribution)

DATA FORMAT: JSON Lines (.jsonl) with structured fields for programmatic access