---
license: mit
task_categories:
- token-classification
language:
- uz
tags:
- chemistry
- biology
- legal
- art
- code
- medical
- music
- finance
pretty_name: Uzbek NER
size_categories:
- 10K<n<100K
---
# Uzbek NER Dataset

## About the Dataset

This dataset is created for Named Entity Recognition (NER) in Uzbek texts. The dataset includes named entities from various categories such as persons, places, organizations, dates, and more.

## Data Structure

The data is provided in JSON format with the following structure:

```json
{
    "LOC": ["Location names"],
    "ORG": ["Organization names"],
    "PERSON": ["Person names"],
    "DATE": ["Date expressions"],
    "MONEY": ["Monetary amounts"],
    "PERCENT": ["Percentage values"],
    "QUANTITY": ["Quantities"],
    "TIME": ["Time expressions"],
    "PRODUCT": ["Product names"],
    "EVENT": ["Event names"],
    "WORK_OF_ART": ["Work of art titles"],
    "LANGUAGE": ["Language names"],
    "CARDINAL": ["Cardinal numbers"],
    "ORDINAL": ["Ordinal numbers"],
    "NORP": ["Nationalities or religious/political groups"],
    "FACILITY": ["Facility names"],
    "LAW": ["Laws or regulations"],
    "GPE": ["Countries, cities, states"]
}
```

## Preparation Guidelines

The following guidelines were followed in preparing this dataset:

1. All possible NERs were extracted from the text (approximately 80%-90%).
2. NERs are provided in their original form without additional annotations or translations.

## Examples

Here are some examples of NER categories:

- **LOC (Location names):** ["Tashkent", "Uzbekistan"]
- **ORG (Organization names):** ["XDP", "Uzbekistan Ministry of Culture"]
- **PERSON (Person names):** ["Ozodbek Nazarbekov", "Ibrat Safo"]
- **DATE (Date expressions):** ["2022", "2024"]
- **MONEY (Monetary amounts):** ["2 billion som", "25 trillion som"]
- **PERCENT (Percentage values):** ["3%", "5%"]
- **QUANTITY (Quantities):** ["100 tons", "200 liters"]
- **TIME (Time expressions):** ["5 minutes", "2 hours"]
- **PRODUCT (Product names):** ["Toyota", "iPhone 13"]
- **EVENT (Event names):** ["Uzbekistan Championship", "Uzbekistan Cup"]
- **WORK_OF_ART (Work of art titles):** ["Song", "Book"]
- **LANGUAGE (Language names):** ["Uzbek", "English"]
- **CARDINAL (Cardinal numbers):** ["one", "two"]
- **ORDINAL (Ordinal numbers):** ["first", "second"]
- **NORP (Nationalities or religious/political groups):** ["Uzbeks", "Russians"]
- **FACILITY (Facility names):** ["Children's Health Clinic", "Tashkent Aviation Institute"]
- **LAW (Laws or regulations):** ["Constitution", "Law"]
- **GPE (Countries, cities, states):** ["Uzbekistan", "Kokand"]

## Download

You can download this dataset using the following code:

```python
from datasets import load_dataset

dataset = load_dataset("risqaliyevds/uzbek_ner")
```

## License

This dataset is provided as open source and is available for free use by all users.

## Contact

If you have any questions or need more information, please contact us.
LinkedIn: [Riskaliev Murad](https://www.linkedin.com/in/risqaliyevds/)