Datasetpublic

uznlp-uz/uzbek_NER

Uzbek NER Gold Uzbek NER Gold is a token-level named entity recognition dataset for Uzbek. The dataset is distributed as a UTF-8 TSV file and uses BIO tagging for named entities. Dataset Summary Dataset ID: uznlp-uz/uzbek_NER Language: Uzbek (uz) Rows: 59,569 token rows Columns: 5 Sentences: 4,176 Split: train Format: UTF-8 TSV Data file: Uzbek_NER_Gold.tsv License: CC BY 4.0 Data Fields Field Description Sentence Sentence identifier.… See the full description on the dataset page: https://huggingface.co/datasets/uznlp-uz/uzbek_NER.

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Dataset Card

Uzbek NER Gold

Uzbek NER Gold is a token-level named entity recognition dataset for Uzbek. The dataset is distributed as a UTF-8 TSV file and uses BIO tagging for named entities.

Dataset Summary

—Dataset ID: uznlp-uz/uzbek_NER
—Language: Uzbek (uz)
—Rows: 59,569 token rows
—Columns: 5
—Sentences: 4,176
—Split: train
—Format: UTF-8 TSV
—Data file: Uzbek_NER_Gold.tsv
—License: CC BY 4.0

Data Fields

Field	Description
`Sentence`	Sentence identifier. Tokens with the same value belong to the same sentence.
`TokenOrder`	1-based token position inside the sentence.
`Token`	Token text.
`NER_Tag`	BIO named entity tag. `O` marks tokens outside named entities.
`pos`	Source POS or token category label.

Tagset

The dataset uses BIO labels over the following named entity types.

Entity	Tag	Gold v1.0 guideline
Person	`PER`	Inson ismi yoki aniq shaxs nomi; lavozim, kasb, umumiy guruh va olmoshlar PER emas.
Organization	`ORG`	Tashkilot, vazirlik, universitet, agentlik, kompaniya, qo‘mita, fond/jamg‘arma va boshqalar.
Location	`LOC`	Davlat, respublika, viloyat, shahar, tuman, geografik joy nomlari.
Miscellaneous	`MISC`	Qolgan maxsus nomlangan obyektlar; aniq sinfga tushmaydigan nomlar.
Money	`MONEY`	Pul birliklari va pul miqdorlari.
Number	`NUMERIC`	Son, raqam, miqdor ifodalari, money/time bo‘lmagan raqamli birliklar.
Date/Time	`TEMPORAL`	Sana, vaqt, davr, yil, oy, kun va vaqt oralig‘i.
Work	`WORK`	Asar, kitob, film, loyiha, badiiy yoki ilmiy ish nomlari; standart yozilishi WORK.

Label Values

NER labels: O, B-PER, I-PER, B-ORG, I-ORG, B-LOC, I-LOC, B-MISC, I-MISC, B-MONEY, I-MONEY, B-NUMERIC, I-NUMERIC, B-TEMPORAL, I-TEMPORAL, B-WORK, I-WORK

POS/category labels: C, IB, II, JJ, MD, N, NER, NUM, P, PUNCT, Prt, RR, UH, UNK, VB

Statistics

Overview

Metric	Value
Token rows	59,569
Columns	5
Sentences	4,176
Unique tokens, case-sensitive	14,791
Unique tokens, case-folded	13,969
Duplicate rows	0
Empty values	0
Minimum sentence length	1
Maximum sentence length	253
Mean sentence length	14.26
Median sentence length	12

Entity Span Distribution

Entity type	Gold v1.0 spans	Original spans	Difference
`LOC`	2,302	2,262	40
`ORG`	2,148	2,207	-59
`PER`	1,653	2,845	-1,192
`MISC`	1,400	1,498	-98
`TEMPORAL`	591	615	-24
`NUMERIC`	581	591	-10
`WORK`	441	465	-24
`MONEY`	134	140	-6
Total	9,250	10,623	-1,373

NER Tag Distribution

NER tag	Count
`O`	43,445
`B-LOC`	2,302
`I-ORG`	2,191
`B-ORG`	2,148
`B-PER`	1,653
`B-MISC`	1,400
`I-MISC`	1,258
`I-PER`	1,161
`I-LOC`	842
`B-TEMPORAL`	591
`B-NUMERIC`	581
`I-WORK`	448
`B-WORK`	441
`I-NUMERIC`	437
`I-TEMPORAL`	323
`I-MONEY`	214
`B-MONEY`	134

POS/Category Distribution

POS/category	Count
`N`	17,733
`NER`	12,914
`VB`	9,746
`PUNCT`	4,628
`JJ`	4,096
`IB`	2,676
`II`	2,137
`C`	1,478
`P`	1,328
`RR`	1,207
`NUM`	956
`MD`	417
`Prt`	225
`UNK`	26
`UH`	2

Normalization

—Text is stored as UTF-8.
—Uzbek text is normalized to Latin script.
—Uzbek apostrophes were normalized to distinct Unicode characters: ‘ for o‘/g‘ and ’ for the tutuq sign.
—Non-standard apostrophe variants were removed from the released TSV.
—Each token is stored on a separate TSV row.
—No field contains empty values in the released file.

Loading

python

from datasets import load_dataset

dataset = load_dataset("uznlp-uz/uzbek_NER", split="train")
print(dataset[0])

The TSV file can also be loaded directly:

python

from datasets import load_dataset

dataset = load_dataset(
    "csv",
    data_files="Uzbek_NER_Gold.tsv",
    delimiter="\t",
    split="train",
)

Intended Use

This dataset can be used for Uzbek named entity recognition research and development, including token classification, NER model training, NER evaluation, information extraction, and benchmarking Uzbek language models.

Notes

The dataset is sentence-aware through the Sentence and TokenOrder fields. To reconstruct sentences, group rows by Sentence and sort them by TokenOrder.

The NER_Tag field follows BIO notation. A tag beginning with B- starts an entity span, and a tag beginning with I- continues an entity span of the same type.

Citation

If you use Uzbek NER Gold, cite the dataset repository:

bibtex

@misc{uzbek_ner_gold,
  title = {Uzbek NER Gold},
  author = {{Elov B.B., Alaev R.H.}},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/uznlp-uz/uzbek_NER}},
  license = {CC BY 4.0}
}