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---
language:
- ar
size_categories:
- 1M<n<10M
task_categories:
- text-generation
dataset_info:
features:
- name: filename
dtype: string
- name: cleaned_sentence
dtype: string
splits:
- name: train
num_bytes: 924672739
num_examples: 1042698
- name: test
num_bytes: 1789952
num_examples: 2485
download_size: 354596619
dataset_size: 926462691
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# 📚 Sadeed Tashkeela Arabic Diacritization Dataset
The **Sadeed** dataset is a large, high-quality Arabic diacritized corpus optimized for training and evaluating Arabic diacritization models.
It is built exclusively from the [Tashkeela corpus](https://sourceforge.net/projects/tashkeela/) for the training set and a refined version of the [Fadel Tashkeela test set](https://github.com/AliOsm/arabic-text-diacritization) for the test set.
## Dataset Overview
- **Training Data**:
- **Source**: Cleaned version of the Tashkeela corpus (original data is ~75 million words, mostly Classical Arabic, with ~1.15% Modern Standard Arabic).
- **Total Examples**: 1,042,698
- **Total Words**: ~53 million
- **Testing Data**:
- **Source**: Corrected version of the Fadel Tashkeela test set, addressing inconsistencies in handling *iltiqā` as-sākinayn* (adjacent consonants without intervening vowels).
- **Total Examples**: 2485 samples
- **Notes**: The test set is refined for phonological consistency according to standard Arabic rules.
- **Features**:
- Fully normalized Arabic text
- Minimal missing diacritics
- Chunked into coherent samples (50–60 words)
- Designed to preserve syntactic and contextual dependencies
---
## Preprocessing Details
### 1. Text Cleaning
- **Diacritization Corrections**:
- Unified diacritization style.
- Corrected diacritization of frequent errors.
- Resolved inconsistencies in *iltiqa' assakinayn* (consonant cluster rules) based on standard phonological rules.
- **Normalization**:
- Applied a comprehensive preprocessing pipeline inspired by [Kuwain](https://github.com/misraj-ai/Kuwain-Arabic-cleaner), preserving non-Arabic characters and symbols.
- **Consistency**:
- Additional normalization steps to ensure stylistic and grammatical consistency across the dataset.
### 2. Text Chunking
- Segmented into samples of **50–60 words** each.
- Used a hierarchical strategy prioritizing natural linguistic breaks, focusing on stronger punctuation first (e.g., sentence-ending punctuation, then commas).
- Designed to preserve the syntactic and contextual coherence of text chunks.
### 3. Dataset Filtering
- **Missing Diacritics**:
- Excluded samples with more than two undiacritized words.
- **Partial Diacritics**:
- Removed samples with three or more partially diacritized words.
- **Test Set Overlap**:
- Eliminated overlapping examples with the Fadel Tashkeela test set, reducing overlap to only **0.4%**.
---
## Usage
This dataset is ideal for:
- **Training**: Using the cleaned Tashkeela corpus to train models for Arabic diacritization.
- **Testing**: Evaluating diacritization systems with the refined Fadel Tashkeela test set.
- Arabic NLP tasks that require fully vocalized texts.
---
## Evaluation Code
The evaluation code for this dataset is available at:
https://github.com/misraj-ai/Sadeed
---
## 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},
url={https://huggingface.co/papers/2504.21635},
}
```
---
## License
This dataset is distributed for **research purposes only**.
Please review the original [Tashkeela corpus license](https://sourceforge.net/projects/tashkeela/) for terms of use. |