Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
Ukrainian
Size:
10M - 100M
License:
File size: 1,806 Bytes
2cbc1a5 e2c7385 2cbc1a5 e2c7385 f664b69 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 827986534
num_examples: 47982455
download_size: 429416941
dataset_size: 827986534
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: apache-2.0
task_categories:
- token-classification
language:
- uk
size_categories:
- 10M<n<100M
tags:
- silver-standard
- ukrainian
- NER
---
# UberText-NER-Silver
**UberText-NER-Silver** is a silver-standard named entity recognition (NER) dataset for the Ukrainian language. It was automatically annotated using a high-performance model trained on NER-UK 2.0 and covers over 2.5 million social media and web sentences. The dataset significantly expands the coverage of underrepresented entity types and informal domains.
## Dataset Summary
- **Total Sentences:** 2,573,205
- **Total Words:** 45,489,533
- **Total Entity Spans:** 4,393,316
- **Entity Types (13):** `PERS`, `ORG`, `LOC`, `DATE`, `TIME`, `JOB`, `MON`, `PCT`, `PERIOD`, `DOC`, `QUANT`, `ART`, `MISC`
- **Format:** IOB-style, token-level annotations
## Source
Texts were taken from the UberText 2.0 corpus social media part, filtered and preprocessed for noise reduction and duplication. The dataset includes both entity-rich and entity-free content to improve model generalization.
## Example Usage
```python
from datasets import load_dataset
dataset = load_dataset("lang-uk/UberText-NER-Silver", split="train")
print(dataset[0])
```
## Applications
- Training large-scale NER models for Ukrainian
- Improving performance in low-resource and informal text domains
- Cross-lingual or transfer learning experiments
## Authors
[Vladyslav Radchenko](https://huggingface.co/pofce), [Nazarii Drushchak](https://huggingface.co/ndrushchak) |