Ahmed

language:
  - egy
  - en
  - de
license: cc-by-sa-4.0
task_categories:
  - translation
  - text-generation
tags:
  - ancient-egyptian
  - hieroglyphics
  - egyptology
  - middle-egyptian
  - demotic
  - late-egyptian
  - historical-linguistics
  - multilingual
  - dictionary
pretty_name: Ancient Egyptian Multilingual Corpus
size_categories:
  - 100K<n<1M
formats:
  - arrow
  - json
  - csv

🏛️ Ancient Egyptian Multilingual Corpus

Dataset Description

A comprehensive multilingual corpus of Ancient Egyptian texts combining multiple authoritative sources, including dictionaries and translated texts from German to English. Available in multiple formats for maximum accessibility.

📊 Dataset Summary

This dataset combines:

Dictionary Sources (3 sources, ~15,000 entries):
- Vygus Egyptian Dictionary 2015 (Mark Vygus)
- Dickson Dictionary of Middle Egyptian
- Ancient Egypt Dictionary (10,000+ words from Gardiner, Faulkner, etc.)
Translated Corpora (4 sources, ~65,000 entries):
- BBAW Egyptian Corpus (35,503 entries)
- TLA Demotic (13,383 entries)
- TLA Earlier Egyptian (12,773 entries)
- TLA Late Egyptian (3,606 entries)

Total: ~80,000+ entries covering 4,000 years of Egyptian language history.

📦 Available Formats

This dataset is available in multiple formats for maximum compatibility:

Format	Description	Best For	Size
Arrow	Native HuggingFace format	Fast loading, memory-efficient processing	Smallest
JSON	Human-readable, structured	Data exploration, custom processing	Medium
CSV	Tabular format	Spreadsheet software, basic analysis	Medium
ZIP	All formats compressed	Offline use, complete download	Compressed

Loading Examples

Arrow Format (Recommended)

from datasets import load_dataset
dataset = load_dataset("AhmedElTaher/ancient-egyptian-multilingual")

JSON Format

import json
with open('ancient-egyptian-multilingual_full.json', 'r', encoding='utf-8') as f:
    data = json.load(f)

CSV Format

import pandas as pd
df = pd.read_csv('ancient-egyptian-multilingual_full.csv')

🎯 Supported Tasks

Ancient Egyptian to English translation
Hieroglyphic text analysis
Historical linguistics research
Egyptological studies
Language model training for ancient languages
Comparative linguistics
Digital humanities research

🌍 Languages

egy: Ancient Egyptian (hieroglyphic, hieratic, demotic scripts)
en: English (translations)
de: German (original translations in TLA/BBAW datasets)

Dataset Structure

📝 Data Fields

Field	Type	Description
`id`	string	Unique identifier for each entry
`transliteration_unicode`	string	Unicode transliteration (ꜣ, ꜥ, ḥ, ḫ, ẖ, š, ṯ, ḏ, ỉ)
`transliteration_mdc`	string	MDC ASCII-compatible transliteration
`translation_en`	string	English translation
`translation_de`	string	German translation (where available)
`hieroglyphs`	string	Hieroglyphic representation (Unicode/Gardiner codes)
`source`	string	Original dataset source
`pos`	string	Part of speech (where available)
`lemmatization`	string	Lemma information (where available)
`grammatical_info`	string	Additional grammatical information

📈 Data Splits

Split	Entries	Percentage
Train	~72,000	90%
Validation	~8,000	10%

Dataset Creation

🔨 Processing Pipeline

PDF Parsing: Custom parsers for dictionary formats
Transliteration: Bidirectional Unicode ↔ MDC conversion
Translation: NLLB-200 neural translation (DE→EN)
Standardization: Unified column names and formats
Validation: Manual checking of sample entries
Multi-format Export: Arrow, JSON, CSV formats

📚 Source Data

Dictionary Sources

Vygus Dictionary 2018 - R.H. Barnhart
Dickson Dictionary - Paul Dickson (2006)
Ancient Egypt Dictionary - ancient-egypt.co.uk

Corpus Sources

BBAW - Berlin-Brandenburg Academy of Sciences
TLA - Thesaurus Linguae Aegyptiae

Usage Guidelines

🚀 Quick Start

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("AhmedElTaher/ancient-egyptian-multilingual")

# Access a sample
sample = dataset['train'][0]
print(f"Egyptian (Unicode): {sample['transliteration_unicode']}")
print(f"Egyptian (MDC): {sample['transliteration_mdc']}")
print(f"English: {sample['translation_en']}")
print(f"Hieroglyphs: {sample['hieroglyphs']}")

🔍 Filtering Examples

# Find all entries with pharaoh
pharaoh_entries = dataset.filter(lambda x: 'pharaoh' in x['translation_en'].lower())

# Get only Demotic texts
demotic = dataset.filter(lambda x: 'demotic' in x['source'])

# Get entries with hieroglyphs
with_hieroglyphs = dataset.filter(lambda x: x['hieroglyphs'] != '')

License & Attribution

📜 License

CC BY-SA 4.0 (Creative Commons Attribution-ShareAlike 4.0 International)

This requires:

✅ Attribution to original sources
✅ Indication of changes
✅ ShareAlike distribution

📚 Required Citations

@dataset{egyptian_multilingual_corpus_2025,
  author = {El Taher, Ahmed},
  title = {Ancient Egyptian Multilingual Corpus},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/AhmedElTaher/ancient-egyptian-multilingual},
  email = {ahmed.g.eltaher@gmail.com}
}

[Additional citations for BBAW, TLA, etc...]

Additional Information

👤 Dataset Curator

Ahmed El Taher
📧 ahmed.g.eltaher@gmail.com
🤗 AhmedElTaher

🤝 Contributions

Contributions welcome! Please submit issues or pull requests.

⚠️ Limitations

Machine translations may contain inaccuracies
Some hieroglyphic representations incomplete
Chronological periods mixed in combined dataset
Reflects historical biases in sources

🙏 Acknowledgments

Special thanks to all contributing institutions and researchers.

Dataset Version: 1.0.0 | Last Updated: 2025-08-14