
# Uyghur NER dataset

## Description

This dataset is in [WikiAnn](https://huggingface.co/datasets/wikiann) format. The dataset is assembled from named entities parsed from Wikipedia, Wiktionary and Dbpedia. For some words, new case forms have been created using [Apertium-uig](https://github.com/apertium/apertium-uig). Some locations have been translated using the Google Translate API.

The dataset is divided into two parts: `train` and `extra`. `Train` has full sentences, `extra` has only named entities.

Tags: `O (0), B-PER (1), I-PER (2), B-ORG (3), I-ORG (4), B-LOC (5), I-LOC (6)`

## Data example

```
{
	'tokens': ['قاراماي', 'شەھىرى', '«مەملىكەت', 'بويىچە', 'مىللەتل…'],
 	'ner_tags': [5, 0, 0, 0, 0],
 	'langs': ['ug', 'ug', 'ug', 'ug', 'ug'],
 	'spans': ['LOC: قاراماي']
}
```

## Usage with `datasets` library

```py
from datasets import load_dataset

dataset = load_dataset("codemurt/uyghur_ner_dataset") 
```
task_categories:token-classification size_categories:n<1K language:ug license:mit region:us
{"language": ["ug"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["token-classification"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "extra", "path": "data/extra-*"}]}], "dataset_info": {"features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": "int64"}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 538947, "num_examples": 473}, {"name": "extra", "num_bytes": 11497, "num_examples": 109}], "download_size": 140314, "dataset_size": 550444}}
TAGS
#task_categories-token-classification #size_categories-n<1K #language-Uighur #license-mit #region-us 


# Uyghur NER dataset

## Description

This dataset is in WikiAnn format. The dataset is assembled from named entities parsed from Wikipedia, Wiktionary and Dbpedia. For some words, new case forms have been created using Apertium-uig. Some locations have been translated using the Google Translate API.

The dataset is divided into two parts: 'train' and 'extra'. 'Train' has full sentences, 'extra' has only named entities.

Tags: 'O (0), B-PER (1), I-PER (2), B-ORG (3), I-ORG (4), B-LOC (5), I-LOC (6)'

## Data example



## Usage with 'datasets' library


# Uyghur NER dataset ## Description

This dataset is in WikiAnn format. The dataset is assembled from named entities parsed from Wikipedia, Wiktionary and Dbpedia. For some words, new case forms have been created using Apertium-uig. Some locations have been translated using the Google Translate API.

The dataset is divided into two parts: 'train' and 'extra'. 'Train' has full sentences, 'extra' has only named entities.

Tags: 'O (0), B-PER (1), I-PER (2), B-ORG (3), I-ORG (4), B-LOC (5), I-LOC (6)' ## Data example ## Usage with 'datasets' library
TAGS
#task_categories-token-classification #size_categories-n<1K #language-Uighur #license-mit #region-us 
 # Uyghur NER dataset ## Description

This dataset is in WikiAnn format. The dataset is assembled from named entities parsed from Wikipedia, Wiktionary and Dbpedia. For some words, new case forms have been created using Apertium-uig. Some locations have been translated using the Google Translate API.

The dataset is divided into two parts: 'train' and 'extra'. 'Train' has full sentences, 'extra' has only named entities.

Tags: 'O (0), B-PER (1), I-PER (2), B-ORG (3), I-ORG (4), B-LOC (5), I-LOC (6)' ## Data example ## Usage with 'datasets' library