Datasets:
🇰🇿 Kazakh-Russian Code-Switching Normalization Dataset
Dataset Summary
Kazakh-Russian Code-Switching Normalization Dataset is a bilingual instruction-following dataset designed for identifying and rewriting Kazakh-Russian mixed-language text into clean Kazakh.
The dataset focuses on informal communication, where Kazakh speakers may naturally mix Russian and Kazakh in one message. Each sample contains a prompt with code-switching, a response that identifies the Russian words or phrases, and a corrected Kazakh version of the original message.
📊 Dataset Statistics
General Metrics
| Metric | Count |
|---|---|
| Total Samples | 300 |
| Total Words (approx.) | 34,317 |
| Avg. Words per Sample | 114 |
Word Count Distribution Per Field
The following table details the distribution of word counts across different fields in the dataset.
| Field | Mean | Median | Min | Max | Total Words |
|---|---|---|---|---|---|
| domain | 2.0 | 2.0 | 2 | 2 | 600 |
| prompt | 31.1 | 30.0 | 20 | 50 | 9,323 |
| response | 80.3 | 78.0 | 49 | 138 | 24,094 |
| sample_id | 1.0 | 1.0 | 1 | 1 | 300 |
Dataset Structure
Each dataset instance contains an informal mixed-language prompt, a detailed response, a domain label, and a sample identifier.
Data Fields
sample_id: A unique identifier for each sample.prompt: The original informal user text. The prompt usually contains Kazakh-Russian code-switching, where Russian words, phrases, or full clauses appear inside a Kazakh-language message.response: The expected answer. This field identifies the Russian-language parts of the prompt and provides a corrected version written fully in Kazakh.domain: The communication domain of the sample. In this dataset, the domain is Informal Communication.
Data Instance
Below is one representative example from the dataset.
{
"sample_id": "1",
"prompt": "Ребят, посоветуйте хороший онлайн-курс по IT. Менің ойымша, қазіргі уақытта бұл өте қажетті мамандық. Хочу освоить что-то новое, развиваться в этом направлении. Қайсысы тиімдірек, ақшаға тұра ма?",
"response": "Бұл сөйлемде орыс тіліндегі 'ребят', 'посоветуйте хороший онлайн-курс по IT', 'хочу освоить что-то новое, развиваться в этом направлении' сияқты сөздер мен тіркестер қолданылған. Сөйлемнің мәтінін толық қазақшаға аудару арқылы тілдің тазалығын қамтамасыз етуге болады. Дұрыс нұсқа: 'Достар, IT бойынша жақсы онлайн-курс кеңес беріңіздерші. Менің ойымша, қазіргі уақытта бұл өте қажетті мамандық. Жаңа нәрсені үйреніп, осы бағытта дамығым келеді. Қайсысы тиімдірек, ақшасына тұра ма?'",
"domain": "Informal Communication"
}
Funding
This dataset was developed as part of the project funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan under Grant No. BR24993001, “Creation of a Large Language Model (LLM) to Support the Kazakh Language and Advance Technological Development.”
Citation
If you use this dataset in your research, please cite the following article:
APA
Kadyrbek, N., Tuimebayev, Z., Mansurova, M., & Viegas, V. (2025). The development of small-scale language models for low-resource languages, with a focus on Kazakh and direct preference optimization. Big Data and Cognitive Computing, 9(5), 137. https://doi.org/10.3390/bdcc9050137
BibTeX
@article{kadyrbek2025development,
title = {The Development of Small-Scale Language Models for Low-Resource Languages, with a Focus on Kazakh and Direct Preference Optimization},
author = {Kadyrbek, Nurgali and Tuimebayev, Zhanseit and Mansurova, Madina and Viegas, Vitor},
journal = {Big Data and Cognitive Computing},
volume = {9},
number = {5},
pages = {137},
year = {2025},
publisher = {MDPI},
doi = {10.3390/bdcc9050137},
url = {https://www.mdpi.com/2504-2289/9/5/137}
}
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