| --- |
| language: |
| - en |
| - ar |
| - ru |
| - es |
| - fr |
| - de |
| - it |
| - pt |
| - ko |
| - zh |
| - ja |
| - hi |
| - bn |
| - tr |
| - id |
| - sv |
| - nl |
| - pl |
| - vi |
| license: cc-by-4.0 |
| task_categories: |
| - translation |
| - text-classification |
| tags: |
| - frequency |
| - dictionary |
| - transliteration |
| - romanization |
| - pos-tagging |
| --- |
| |
| # Multilingual Core Vocabulary 🌍 |
|
|
| This dataset contains millions of frequency-sorted, highly accurate words across 19 languages. It is designed to be the ultimate resource for building cross-lingual applications, AI similarity agents, and translation models. |
|
|
| ## Dataset Structure |
| This repository contains two variations of the dataset: |
| * **Massive_Dataset**: Contains over 6 million words. The words were extracted and frequency-sorted from FastText, cleaned from internet noise using official Hunspell dictionaries, translated using Meta's NLLB-600M AI, and Romanized using specialized linguistic libraries. |
| * **Balanced_Dataset**: Contains highly accurate core vocabulary cross-referenced against Facebook MUSE bilingual dictionaries for perfect 1-to-1 translations. |
|
|
| ## Features (Columns) |
| - `Word`: The original word in its native script. |
| - `Pronunciation`: Romanized English representation of the phonetic pronunciation (e.g., Pinyin for Chinese, Romaji for Japanese). |
| - `POS_Tag`: The Universal Part-of-Speech tag (e.g., NOUN, VERB, ADJ) generated using the spaCy English NLP model. |
| - `Translation`: English meaning of the word. |
|
|
| ## Languages Included |
| Arabic, Russian, Spanish, French, German, Italian, Portuguese, Korean, Chinese, Japanese, Hindi, Bengali, Turkish, Indonesian, Swedish, Dutch, Polish, Vietnamese, and English. |
|
|
| ## Pipeline Overview |
| 1. **Extraction**: Top words scraped from Common Crawl / Wikipedia via FastText. |
| 2. **Filtration**: Strict dictionary validation using Linux `Hunspell` (removed 15+ million invalid tokens/emojis). |
| 3. **Translation**: GPU-accelerated translation via Meta's `NLLB-200-distilled-600M`. |
| 4. **Romanization**: Custom phonetic transliteration using `pypinyin`, `pykakasi`, `transliterate`, and `indic-transliteration`. |
| 5. **POS Tagging**: English translations were tagged using `en_core_web_sm` (spaCy) to provide a unified grammatical classification across all languages. |
|
|
