| --- |
| language: |
| - kk |
| - ru |
| license: cc-by-nc-4.0 |
| task_categories: |
| - text-generation |
| tags: |
| - kazakh |
| - russian |
| - code-switching |
| - language-normalization |
| - kazakh-language |
| - informal-communication |
| - text-rewriting |
| - instruction-following |
| - low-resource-language |
| pretty_name: Kazakh-Russian Code-Switching Normalization Dataset |
| size_categories: |
| - n<1K |
| --- |
| |
| # 🇰🇿 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. |
|
|
| ```json |
| { |
| "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](https://doi.org/10.3390/bdcc9050137) |
|
|
| ### BibTeX |
|
|
| ```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} |
| } |
| ``` |
|
|
