Datasets:
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Please provide your real details when requesting access.
The owner of the dataset reserves the right to reject any request without
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dataset_info:
- config_name: kk_en
features:
- name: kk
dtype: string
- name: en
dtype: string
splits:
- name: train
num_bytes: 679627
num_examples: 2055
download_size: 406306
dataset_size: 679627
- config_name: kk_ru
features:
- name: kk
dtype: string
- name: ru
dtype: string
splits:
- name: train
num_bytes: 4216168
num_examples: 12049
download_size: 2290719
dataset_size: 4216168
configs:
- config_name: kk_en
data_files:
- split: train
path: kk_en/train-*
- config_name: kk_ru
data_files:
- split: train
path: kk_ru/train-*
default: true
task_categories:
- translation
language:
- kk
- ru
pretty_name: Kazakh parallel corpus for various languages
size_categories:
- 10K<n<100K
🔄 Updates
- 2025-12-04: Added a new set of Kazakh–English sentence pairs.
KazParov
KazParov—short for Kazakh parallel corpus for various languages—is a Kazakh-centred parallel corpus aligned with multiple languages. The name is pronounced like the surname of Garry Kasparov, the legendary chess grandmaster.
At the current stage, the corpus consists predominantly of Kazakh–Russian sentence pairs. This is due to the relative accessibility of high-quality Kazakh–Russian parallel data compared to, for example, Kazakh–English material. However, since Russian is a high-resource language comparable to English, it may also serve as a useful pivot language in future machine translation and cross-lingual NLP research. Importantly, KazParov is not a synthetic corpus—all sentence pairs are sourced from real texts rather than machine-generated data.
The corpus is released strictly for research and educational purposes only. Any form of commercial use, redistribution for profit, or integration into proprietary systems is not permitted.
Initiated independently during a period of unemployment, KazParov represents one of several personal efforts (e.g, KazLibri) to enrich Kazakh text and speech resources through perseverance and self-driven research. Please excuse the gradual pace of its expansion and updates, as the project is currently being developed single-handedly.
Please also note that the corpus is not entirely error-free, although considerable effort has been made to review, correct, and refine sentence pairs. The primary focus during data collection has been to preserve semantic equivalence rather than strict grammatical or orthographic accuracy. Should you notice any errors or inconsistencies, your feedback and suggestions will be sincerely appreciated.