---
language:
- ar
- en
license: apache-2.0
task_categories:
- translation
tags:
- egyptian-arabic
- arabic
- english
- bilingual
- translation-pairs
- arabic-nlp
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: English
    dtype: string
  - name: Translation
    dtype: string
  - name: language
    dtype: string
  splits:
  - name: train
    num_bytes: 4774326
    num_examples: 8118
  download_size: 2548714
  dataset_size: 4774326
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Bilingual Egyptian Dataset

## Dataset Description

This dataset contains **bilingual text pairs** in **English** and **Egyptian Arabic / Modern Standard Arabic**. Each entry provides parallel translations covering a wide range of everyday and specialized domains, making it valuable for translation models, multilingual NLP research, and general Arabic language applications.

### Key Features

- **Languages**: English ↔ Egyptian Arabic (العامية المصرية) & Arabic (العربية)
- **Domain**: Multi-domain (general, social, cultural, professional, and more)
- **Format**: Parallel text pairs with language variant labeling
- **Content**: Diverse topics spanning everyday conversation to specialized domains
- **Quality**: Professional-level translations maintaining context and meaning
- **Size**: 8,630 parallel pairs

## Dataset Structure

### Data Fields

- **`English`**: Content written in English
- **`Translation`**: Corresponding translation in Egyptian Arabic or Arabic dialect
- **`language`**: Language variant of the translation — either `Egyptian Arabic` or `Arabic`

### Example

```json
{
  "English": "What are the specific steps to inquire about the Integrated Services Card via the Ministry of Social Solidarity's website using the National ID?",
  "Translation": "إيه هي الخطوات المحددة للاستعلام عن كارت الخدمات المتكاملة من خلال الـ website بتاع وزارة التضامن الاجتماعي بالرقم القومي؟",
  "language": "Egyptian Arabic"
}
```

```json
{
  "English": "The acquisition of knowledge is a lifelong journey that empowers individuals to critical thinking, problem-solving, and innovation, ultimately serving as the bedrock for a nation's progress and its ability to adapt to global challenges like Climate Change or Economic Shifts, fostering sustainable development.",
  "Translation": "اكتساب المعرفة هو رحلة مدى الحياة تمكّن الأفراد من التفكير النقدي وحل المشكلات والابتكار، مما يخدم في نهاية المطاف كأساس لتقدم الأمة وقدرتها على التكيف مع التحديات العالمية مثل Climate Change أو Economic Shifts، مما يعزز التنمية المستدامة.",
  "language": "Arabic"
}
```

## Usage

### Loading the Dataset

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Omar-youssef/English-Egyptian-Arabic-Translation-Pairs")

# Access the training split
train_data = dataset['train']

print(f"Total examples: {len(train_data)}")  # 8,630

# Example of accessing parallel text pairs
for example in train_data.select(range(3)):
    print(f"English: {example['English']}")
    print(f"Translation: {example['Translation']}")
    print(f"Language: {example['language']}")
    print("-" * 50)
```

## Data Quality Features

- **Natural Translation**: Maintains Egyptian Arabic dialect authenticity where applicable
- **Dialect Coverage**: Includes both Egyptian colloquial Arabic and Modern Standard Arabic
- **Multi-Domain**: Covers a broad range of topics and domains
- **Cultural Context**: Adapts content to Egyptian and Arab cultural context
- **Consistent Terminology**: Uses standardized terminology across domains
- **Comprehensive Coverage**: Spans multiple everyday and specialized topics

## Citation

If you use this dataset in your research, please cite:

```bibtex
@dataset{omar_youssef_bilingual_egyptian,
  author = {Omar Youssef},
  title = {Bilingual Egyptian Arabic Dataset},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/Omar-youssef/English-Egyptian-Arabic-Translation-Pairs},
  note = {English–Egyptian Arabic / Arabic parallel corpus, multi-domain, 8630 pairs}
}
```

## License

This dataset is released under the **Apache 2.0** license, allowing for both research and commercial use.