metadata

annotations_creators:
  - no-annotation
language:
  - uz
license: apache-2.0
multilinguality:
  - monolingual
size_categories:
  - 1M<n<10M
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
pretty_name: UzCrawl
configs:
  - config_name: default
    data_files:
      - split: news
        path: data/news-*
      - split: telegram_blogs
        path: data/telegram_blogs-*
dataset_info:
  features:
    - name: text
      dtype: string
    - name: timestamp
      dtype: string
    - name: source
      dtype: string
  splits:
    - name: news
      num_bytes: 3051717115
      num_examples: 1250018
    - name: telegram_blogs
      num_bytes: 367462330
      num_examples: 368017
  download_size: 1680419450
  dataset_size: 3419179445
tags:
  - uz
  - crawl
  - telegram_blogs

Dataset Card for UzCrawl

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://tahrirchi.uz/grammatika-tekshiruvi
Repository: More Information Needed
Paper: More Information Needed
Point of Contact: More Information Needed
Size of downloaded dataset files: 3.41 GB
Size of the generated dataset: 1.68 GB
Total amount of disk used: 5.1 GB

Dataset Summary

In an effort to democratize research on low-resource languages, we release UzCrawl dataset, a web and telegram crawl corpus consisting of materials from nearly 1.2 million unique sources in the Uzbek Language.

Please refer to our blogpost for further details.

P.S. We updated the dataset with 2nd version that extends the scope to new topics as well as being up to date to March 2024.

To load and use dataset, run this script:

from datasets import load_dataset

uz_crawl=load_dataset("tahrirchi/uz-crawl")

To use v1 of the dataset, run this script instead:

from datasets import load_dataset

uz_crawl=load_dataset("tahrirchi/uz-crawl", revision="b8de928a18559b2a1659124c412ae31c9c238eb8")

Dataset Structure

Data Instances

plain_text

Size of downloaded dataset files: 3.41 GB
Size of the generated dataset: 1.68 GB
Total amount of disk used: 5.1 GB

An example of 'news' looks as follows.

{
    'text': "O‘zbekiston Respublikasi Vazirlar Mahkamasining 2019 yil 24 iyuldagi 620-son qarori bilan tasdiqlangan «Xorijiy davlatlarda ta'lim olganlik to‘g‘risidagi hujjatlarni tan olish tartibi to‘g‘risida»gi Nizom ijrosini ta'minlash maqsadida Ta'lim sifatini nazorat qilish davlat inspeksiyasida (Toshkent shahar, Chilonzor tumani, Nurxon ko‘chasi, 21-uy) 2019 yil 9 –14 sentabr kunlari sohalar bo‘yicha sinov testlari bo‘lib o‘tishi rejalashtirilgan.\nTa'lim sifatini nazorat qilish davlat inspeksiyasi matbuot xizmati xabariga\xa0ko‘ra, «Huquqshunoslik», «Sog‘liqni saqlash va ijtimoiy ta'minot», «Iqtisodiyot», «Qishloq xo‘jaligi, muhandislik, ishlov berish va qurilish» hamda «O‘qituvchilar tayyorlash va pedagogik fanlar» sohalari bo‘yicha sinov testlari o‘tkaziladigan sanasi va sinov testida ishtirok etuvchilar ro‘yxati jadvalga muvofiq belgilanadi.\nTa'lim sifatini nazorat qilish davlat inspeksiyasi ogohlantirishicha, xorijiy davlatlarda ta'lim olganlik to‘g‘risidagi hujjatlarni tan olish uchun belgilangan sinov testlariga o‘z vaqtida kelmagan, sinov testida ishtirok etuvchilar ro‘yxatida mavjud bo‘lmagan talabgorlarga sinovlarga kirishga ruxsat etilmaydi.",
    'timestamp': '2019-06-09',
    'source': 'https://kun.uz/uz/news/2019/09/06/xorijda-talim-olganlik-togrisidagi-hujjatlarni-tan-olish-uchun-testlar-otkaziladigan-kunlar-malum-boldi'
}

Data Fields

The data fields are the same among all splits.

text: a string feature that contains text.
timestamp: a string feature that contains timestamp of the material.
source: a string feature that contains url of the material.

Data Splits

split_name	num_examples
news	1250018
telegram_blogs	368017

Dataset Creation

The news portion have been crawled from 57 different websites using Scrapy framework. And telegram_blogs portion is consisted of manually curated texts from 128 high-quality Telegram channels.

Citation

Please cite this model using the following format:

@online{Mamasaidov2023UzCrawl,
    author    = {Mukhammadsaid Mamasaidov and Abror Shopulatov},
    title     = {UzCrawl dataset},
    year      = {2023},
    url       = {https://huggingface.co/datasets/tahrirchi/uz-crawl},
    note      = {Accessed: 2023-10-28}, % change this date
    urldate   = {2023-10-28} % change this date
}

Gratitude

We are thankful to these awesome organizations and people for helping to make it happen:

Asadbek Kiyomov: for his works on the beginning of the project.
Ilya Gusev: for his advise throughout the process
David Dale: for his advise throughout the process

Contacts

We believe that this work will inspire all enthusiasts around the world to open the hidden beauty of low-resource languages, in particular of Uzbek.

For further development and issues about the dataset, please use [email protected] or [email protected] to contact.

Datasets:

tahrirchi
/

uz-crawl