---
dataset_name: "AraLingBench"
pretty_name: "AraLingBench"
tags:
  - arabic
  - evaluation
  - multiple-choice
  - question-answering
language:
  - ar
task_categories:
  - question-answering
size_categories:
  - n<1K
---

# AraLingBench

📄 **Paper:** [arXiv:2511.14295](https://arxiv.org/abs/2511.14295)  
💻 **GitHub:** [hammoudhasan/AraLingBench](https://github.com/hammoudhasan/AraLingBench)

AraLingBench is a **150-question Arabic multiple-choice benchmark** that tests core linguistic competence of language models across five pillars:

- النحو (Grammar)
- الصرف (Morphology)
- الإملاء (Spelling & Orthography)
- فهم اللغة (Reading Comprehension)
- التركيب اللغوي والأسلوبي (Syntax & Stylistics)

All questions are **human-authored and validated**, with a single correct answer and a difficulty label: `Easy`, `Medium`, or `Hard`.

## Data Fields

Each example has:
- `label` *(str)* — linguistic category
- `context` *(str)* — optional supporting text (may be empty)
- `question` *(str)* — question in Arabic
- `options` *(List[str])* — answer choices
- `answer` *(str)* — correct choice (matches one of `options`)
- `difficulty` *(str)* — one of `Easy`, `Medium`, `Hard`

Single split:
- `train` — 150 examples (use as an evaluation set)

## Usage

```python
from datasets import load_dataset

ds = load_dataset("hammh0a/AraLingBench")
example = ds["train"][0]

print(example["label"])
print(example["question"])
print(example["options"])
print(example["answer"])
```

## Citation

If you use AraLingBench, please cite:

```bibtex
@article{zbib2025aralingbench,
  title        = {AraLingBench: A Human-Annotated Benchmark for Evaluating Arabic Linguistic Capabilities of Large Language Models},
  author       = {Mohammad Zbib and Hasan Abed Al Kader Hammoud and Sina Mukalled and Nadine Rizk and Fatima Karnib and Issam Lakkis and Ammar Mohanna and Bernard Ghanem},
  journal      = {arXiv preprint arXiv:2511.14295},
  year         = {2025},
  url          = {https://arxiv.org/abs/2511.14295}
}
```