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README.md
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path: data/meaning_in_context-*
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- split: fill_in
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path: data/fill_in-*
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---
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path: data/meaning_in_context-*
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- split: fill_in
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path: data/fill_in-*
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license: mit
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task_categories:
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- question-answering
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language:
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- uz
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tags:
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- uzbek
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- linguistics
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pretty_name: uzlib
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size_categories:
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- 1K<n<10K
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---
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# Uzbek Linguistic Benchmark (UzLiB)
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** [hf.co/datasets/murodbek/uzlib](https://huggingface.co/datasets/murodbek/uzlib)
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- **Repository:** [https://github.com/shopulatov/uzlib](https://github.com/shopulatov/uzlib)
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- **Point of Contact:** [ml.muhandis@gmail.com](mailto:ml.muhandis@gmail.com)
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- **Size of downloaded dataset files:** 144 kB
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- **Size of the generated dataset:** 144 kB
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- **Total amount of disk used:** 331 kB
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### Dataset Summary
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The Uzbek Linguistic Benchmark (UzLiB) is a benchmark with multiple-choice questions for evaluating linguistic abilities of Large Language Models (LLMs) in Uzbek language.
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To load and use dataset, run this script:
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```python
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from datasets import load_dataset
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uzlib = load_dataset("murodbek/uzlib")
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```
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## Dataset Structure
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An example of `correct_word` looks as follows.
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```
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{'id': 'CW1242',
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'question': 'Berilgan variantlar orasida qaysi biri to‘g‘ri yozilgan?',
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'option_a': 'Samolyod',
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'option_b': 'Samalyot',
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'option_c': 'Samalyod',
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'option_d': 'Samolyot',
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'answer': 'D',
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'type': 'correct_word'}
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```
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### Data Fields
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The data fields are the same among all splits.
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- `id`: a `string` feature to indicate id of the given question.
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- `question`: a `string` feature to question.
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- `option_a`: a `string` feature to indicate answer option A.
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- `option_b`: a `string` feature to indicate answer option B.
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- `option_c`: a `string` feature to indicate answer option C.
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- `option_d`: a `string` feature to indicate answer option D.
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- `answer`: a `string` feature to indicate the correct answer. One of `A`, `B`, `C` or `D`.
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- `type`: a `string` feature to indicate the type of the question. One of `correct_word`, `meaning`, `meaning_in_context` or `fill_in`.
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### Data Splits
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### Data Splits
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| split_name |num_examples|
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|-----------------|-----------:|
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| correct_word | 1501 |
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| meaning | 236 |
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| meaning_in_context | 72 |
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| fill_in | 52 |
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| **all** | **1861** |
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## Dataset Creation
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The source for all questions is collected from selected 4 Telegram channels quizzes: [Orif Tolib](https://t.me/oriftolib), [Тўғри ёзамиз — мутахассис блоги](https://t.me/xatoliklar), [Tahrir.uz📝](https://t.me/tahrir_uz), and [Tahrirchi | Tilmoch](https://t.me/tahrirchi_uz). Then, each question is manually labeled to record correct answer as Telegram does not provide the correct answers for quizzes. After that, each question went through categorization, transliteration and deduplication processes.
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### Citation Information
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```
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@misc{Shopulatov2025UzLiB,
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title={UzLiB: A benchmark for evaluating Uzbek linguistics},
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author={Abror Shopulatov},
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year={2025}
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url={https://huggingface.co/datasets/murodbek/uzlib},
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note={Accessed: 2025-02-18}, % change this date
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urldate = {2025-02-18}} % change this date
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}
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```
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### Contact
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For any questions or issues related to the dataset or code, please contact [ml.muhandis@gmail.com](mailto:ml.muhandis@gmail.com).
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