---
license: apache-2.0
language:
- uz
- ru
tags:
- ner
- named-entity-recognition
- uzbek
- russian
- pii-detection
- synthetic
- knowledge-distillation
size_categories:
- 100K<n<1M
---

# Rubai NER Dataset - Personal Information Detection (Synthetic)

A dataset for training Named Entity Recognition (NER) models to detect personal information in Uzbek and Russian text. All Data Synthetic, no contains real personal information!

## Dataset Description

This dataset contains **142,704** annotated examples for detecting personal information entities in informal Uzbek and Russian text (Latin and Cyrillic scripts).

### Supported Entity Types

| Entity | Description | Example |
|--------|-------------|---------|
| **NAME** | Personal names | Alisher, Мухаммад |
| **PHONE** | Phone numbers | +998 90 123 45 67 |
| **DATE** | Dates and times | 15-yanvar 2024, 15 января |
| **DOCUMENT_ID** | Document IDs, passport numbers | AA1234567 |
| **ADDRESS** | Physical addresses | Chilonzor 5-kvartal 12-uy |
| **CARD_NUMBER** | Bank card numbers | 8600 1234 5678 9012 |

### Label Distribution

| Label | Count | Percentage |
|-------|-------|------------|
| TEXT | 142,704 | 100.0% |
| ADDRESS | 60,766 | 42.6% |
| DATE | 46,803 | 32.8% |
| PHONE | 45,046 | 31.6% |
| NAME | 36,126 | 25.3% |
| CARD_NUMBER | 32,748 | 22.9% |
| DOCUMENT_ID | 30,984 | 21.7% |

## Data Format

Each entry contains:
- `id`: Unique identifier
- `original`: The original text with entities
- `domain`: Text domain/category
- `labels`: List of entity types present
- `types`: Token-level entity annotations

### Example

```json
{
  "id": 92721,
  "original": "Hujjatlar ro'yxatga olindi. Sizning shaxsiy raqamingiz 59-chi bo'ldi. Bog'lanish uchun telefon raqami 930 24 49 37. Yetkazib berish manzili quyidagicha: sergelida yigirma to'rtinchi uy 10-kvartira. Номер kartani yangilash talab etiladi: 5249 61 80 21 56 0603.",
  "domain": "general",
  "labels": ["TEXT", "DOCUMENT_ID", "PHONE", "ADDRESS", "CARD_NUMBER"],
  "types": ["TEXT", "TEXT", "TEXT", "TEXT", "TEXT", "TEXT", "DOCUMENT_ID", "TEXT", "TEXT", "TEXT", "TEXT", "TEXT", "PHONE", "PHONE", "PHONE", "PHONE", "TEXT", "TEXT", "TEXT", "TEXT", "ADDRESS", "ADDRESS", "ADDRESS", "ADDRESS", "ADDRESS", "TEXT", "TEXT", "TEXT", "TEXT", "TEXT", "CARD_NUMBER", "CARD_NUMBER", "CARD_NUMBER", "CARD_NUMBER", "CARD_NUMBER", "CARD_NUMBER"]
}
```

## Languages

- **Uzbek** (Latin script): Primary language (~70%)
- **Russian** (Cyrillic script): Secondary language (~30%)
- Mixed: Some examples contain both languages

## Use Cases

- PII (Personal Identifiable Information) detection
- Data anonymization
- Privacy protection systems
- Text classification

## Citation

```bibtex
@dataset{rubai_ner_2026,
  title={Rubai NER Dataset for Personal Information Detection},
  author={Islomov},
  year={2026},
  url={https://huggingface.co/datasets/islomov/rubai-NER-150K-Personal}
}
```

## License

Apache 2.0