---
license: cc-by-4.0
language:
  - ur
pretty_name: UrduMMLU
size_categories:
  - 10K<n<100K
task_categories:
  - question-answering
  - multiple-choice
tags:
  - urdu
  - mmlu
  - multiple-choice
  - education
  - benchmark
  - low-resource
configs:
  - config_name: default
    data_files:
      - split: test
        path: urdummlu.json
---

<p align="center">
  <img src="logo.png" alt="UrduMMLU" width="180">
</p>

# UrduMMLU

**UrduMMLU** is a large-scale, human-curated benchmark of **26,431** multiple-choice
questions written natively in Urdu. Questions are drawn from Pakistani secondary and
higher-secondary curricula (SSC-I through HSSC-II) and span the humanities, social
sciences, STEM, professional studies, and general knowledge.

Unlike machine-translated MMLU variants, every item here is sourced from native Urdu
exam material, then cleaned, de-duplicated, schema-normalized, and human-verified
through a multi-stage annotation pipeline.

## Dataset at a glance

| | |
|---|---|
| Questions | 26,431 |
| Language | Urdu (`ur`) |
| Format | Single-answer multiple choice (4–5 options) |
| Levels | SSC-I, SSC-II, HSSC-I, HSSC-II |
| Domains | 5 (26 subdomains) |
| Files | `urdummlu.json`, `stats.json` |

## Schema

Each record in `urdummlu.json` has exactly these fields:

```json
{
  "id": 0,
  "question": "مقبرہ شاہ رکن عالمؒ ____ میں ہے۔",
  "options": { "A": "لاہور", "B": "ساہیوال", "C": "سیالکوٹ", "D": "ملتان" },
  "correct_key": "D",
  "domain": "Social Sciences",
  "subdomain": "pakistan studies",
  "level": "SSC-II",
  "length_tier": "short",
  "source": [
    { "name": "BISE Multan 2025", "url": "https://www.bisemultan.edu.pk" }
  ]
}
```

| Field | Description |
|---|---|
| `id` | Stable integer identifier |
| `question` | Question stem in Urdu |
| `options` | Map of option key (`A`–`E`) to Urdu answer text |
| `correct_key` | Key of the correct option |
| `domain` | Top-level domain (one of 5) |
| `subdomain` | Fine-grained subject (26 total) |
| `level` | Curriculum level: `SSC-I`, `SSC-II`, `HSSC-I`, `HSSC-II` |
| `length_tier` | `short`, `long`, or `null` (question-length bucket) |
| `source` | List of `{name, url}` provenance entries |

## Domain distribution

| Domain | Questions |
|---|---|
| Humanities | 11,010 |
| Social Sciences | 7,968 |
| STEM | 5,113 |
| Other | 1,365 |
| Profession | 975 |

The 26 subdomains include Urdu literature, Urdu language, Islamic studies,
Pakistan studies, chemistry, biology, mathematics, computer science, economics,
sociology, and more. Per-subdomain, per-level, and source counts are in
[`stats.json`](stats.json).

## Curriculum levels

| Level | Questions |
|---|---|
| SSC-I | 11,601 |
| SSC-II | 6,838 |
| HSSC-II | 4,125 |
| HSSC-I | 3,867 |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("MBZUAI/UrduMMLU", split="test")
ex = ds[0]
print(ex["question"])
print(ex["options"], "→", ex["correct_key"])
```

### Evaluation

Treat each item as a single-answer MCQ: present `question` and `options`, then
compare the model's chosen key against `correct_key`. Exact-match accuracy is the
primary metric. We recommend reporting accuracy broken down by `domain` and `level`.

## Sources

Questions were collected from publicly available Urdu exam and practice-question
repositories, including Ustad 360, MCQ Times, TestPoint PK, eTest, FBISE,
ExamAunty, GoTest, PakMCQs, and provincial examination boards (e.g. BISE Multan).
Each item retains its source attribution in the `source` field.

## Limitations

- Answer keys reflect the original source material and the annotation process;
  rare errors may remain.
- `length_tier` is `null` for items where a length bucket was not assigned.
- Coverage is weighted toward humanities and the SSC levels, mirroring the
  availability of native Urdu exam content.

## Citation

```bibtex
@article{tabassum2026urdummlu,
  title     = {{UrduMMLU}: A Massive Multitask Benchmark for {Urdu} Language Understanding},
  author    = {Tabassum, Ahmer and Ahmad, Sarfraz and Iqbal, Hasan and
               Aijaz, Owais and Ahsan, Momina and Nakov, Preslav},
  journal   = {arXiv preprint},
  year      = {2026},
  url       = {https://anonymous.for.review}
}
```

## License

Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).