---
license: mit
language:
- fa
tags:
- ner
- named-entity-recognition
- persian
- farsi
- token-classification
task_categories:
- token-classification
pretty_name: Persian NER Dataset (Synthetic)
---

# Persian NER Dataset (Synthetic)

## Dataset Description

This dataset is a synthetically generated Named Entity Recognition (NER) dataset for the Persian (Farsi) language. It covers a wide range of entity types commonly found in Persian news articles, official documents, and general text.

## Entities Covered

The dataset includes annotations for 23 distinct entity types:

1. **LANGUAGE** - Languages (e.g., فارسی, عربی)
2. **LOCATION** - Locations (e.g., خلیج فارس)
3. **CITY** - Cities (e.g., تهران, شیراز)
4. **PROVINCE** - Provinces (e.g., سیستان و بلوچستان)
5. **FACILITY** - Facilities & landmarks (e.g., برج میلاد)
6. **ORGANIZATION** - Organizations (e.g., سازمان ملل متحد)
7. **PERSON** - People (e.g., حسن روحانی)
8. **EVENT** - Events (e.g., انتخابات ریاست جمهوری)
9. **DATE** - Dates (e.g., ۱۴۰۳/۰۵/۱۰)
10. **TIME** - Times (e.g., ساعت ۱۴:۳۰)
11. **NARCOTICS** - Drugs (e.g., ماری‌جوانا)
12. **WEAPON** - Weapons (e.g., کلاشنیکف)
13. **ALCOHOLIC_BEVERAGES** - Alcohol (e.g., ودکا)
14. **PRODUCT** - Products (e.g., سمند)
15. **MONEY** - Money amounts (e.g., ۱۰۰ میلیون تومان)
16. **PERCENT** - Percentages (e.g., ۵۰ درصد)
17. **POLITICAL_PARTY** - Political parties (e.g., جبهه پایداری)
18. **RELIGION** - Religions (e.g., شیعه)
19. **NATIONALITY** - Nationalities (e.g., ایرانی)
20. **LAW** - Laws (e.g., قانون اساسی)
21. **CULTURAL_CONCEPT** - Cultural concepts (e.g., نوروز)
22. **COUNTY** - Counties (e.g., بخش ماهان)
23. **WEAPON** - Weapons (includes various weapon types)

## Dataset Structure

Each example contains:
- `tokenized_text`: A list of tokens
- `ner`: Annotations with start/end indices and entity types

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("your-username/persian-ner")