---
language:
- ar
size_categories:
- 1K<n<10K
task_categories:
- text-generation
dataset_info:
  features:
  - name: filename
    dtype: string
  - name: output
    dtype: string
  - name: input
    dtype: string
  splits:
  - name: train
    num_bytes: 1446104
    num_examples: 1200
  download_size: 678514
  dataset_size: 1446104
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# SadeedDiac-25: A Benchmark for Arabic Diacritization

[Paper](https://huggingface.co/papers/2504.21635)

**SadeedDiac-25** is a comprehensive and linguistically diverse benchmark specifically designed for evaluating Arabic diacritization models. It unifies Modern Standard Arabic (MSA) and Classical Arabic (CA) in a single dataset, addressing key limitations in existing benchmarks.

## Overview

Existing Arabic diacritization benchmarks tend to focus on either Classical Arabic (e.g., Fadel, Abbad) or Modern Standard Arabic (e.g., CATT, WikiNews), with limited domain diversity and quality inconsistencies. SadeedDiac-25 addresses these issues by:

- Combining MSA and CA in one dataset
- Covering diverse domains (e.g., news, religion, politics, sports, culinary arts)
- Ensuring high annotation quality through a multi-stage expert review process
- Avoiding contamination from large-scale pretraining corpora

## Dataset Composition

SadeedDiac-25 consists of 1,200 paragraphs:

- **📘 50% Modern Standard Arabic (MSA)**

  - 454 paragraphs of curated original MSA content
  - 146 paragraphs from WikiNews
  - Length: 40–50 words per paragraph

- **📗 50% Classical Arabic (CA)**

  - 📖 600 paragraphs from the Fadel test set

## Evaluation Results

We evaluated several models on SadeedDiac-25, including proprietary LLMs and open-source Arabic models. Evaluation metrics include Diacritic Error Rate (DER), Word Error Rate (WER), and hallucination rates.
The evaluation code for this dataset is available at: https://github.com/misraj-ai/Sadeed

### Evaluation Table

| Model                    | DER (CE)   | WER (CE)   | DER (w/o CE) | WER (w/o CE) | Hallucinations |
| ------------------------ | ---------- | ---------- | ------------ | ------------ | -------------- |
| Claude-3-7-Sonnet-Latest | **1.3941** | **4.6718** | **0.7693**   | **2.3098**   | **0.821**      |
| GPT-4                    | 3.8645     | 5.2719     | 3.8645       | 10.9274      | 1.0242         |
| Gemini-Flash-2.0         | 3.1926     | 7.9942     | 2.3783       | 5.5044       | 1.1713         |
| *Sadeed*                 | *7.2915*   | *13.7425*  | *5.2625*     | *9.9245*     | *7.1946*       |
| Aya-23-8B                | 25.6274    | 47.4908    | 19.7584      | 40.2478      | 5.7793         |
| ALLaM-7B-Instruct        | 50.3586    | 70.3369    | 39.4100      | 67.0920      | 36.5092        |
| Yehia-7B                 | 50.8801    | 70.2323    | 39.7677      | 67.1520      | 43.1113        |
| Jais-13B                 | 78.6820    | 99.7541    | 60.7271      | 99.5702      | 61.0803        |
| Gemma-2-9B               | 78.8560    | 99.7928    | 60.9188      | 99.5895      | 86.8771        |
| SILMA-9B-Instruct-v1.0   | 78.6567    | 99.7367    | 60.7106      | 99.5586      | 93.6515        |

> **Note**: CE = Case Ending


## Citation

If you use SadeedDiac-25 in your work, please cite:
## Citation

If you use this dataset, please cite:

```bibtex
@misc{aldallal2025sadeedadvancingarabicdiacritization,
      title={Sadeed: Advancing Arabic Diacritization Through Small Language Model}, 
      author={Zeina Aldallal and Sara Chrouf and Khalil Hennara and Mohamed Motaism Hamed and Muhammad Hreden and Safwan AlModhayan},
      year={2025},
      eprint={2504.21635},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.21635}, 
}
```


## License

📄 This dataset is released under the CC BY-NC-SA 4.0 License.

## Contact

📬 For questions, contact [Misraj-AI](https://misraj.ai/) on Hugging Face.