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---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: question
    dtype: string
  - name: option_a
    dtype: string
  - name: option_b
    dtype: string
  - name: option_c
    dtype: string
  - name: option_d
    dtype: string
  - name: answer
    dtype: string
  - name: type
    dtype: string
  splits:
  - name: correct_word
    num_bytes: 250887
    num_examples: 1501
  - name: meaning
    num_bytes: 49277
    num_examples: 236
  - name: meaning_in_context
    num_bytes: 20488
    num_examples: 72
  - name: fill_in
    num_bytes: 10202
    num_examples: 52
  download_size: 143580
  dataset_size: 330854
configs:
- config_name: default
  data_files:
  - split: correct_word
    path: data/correct_word-*
  - split: meaning
    path: data/meaning-*
  - split: meaning_in_context
    path: data/meaning_in_context-*
  - split: fill_in
    path: data/fill_in-*
license: mit
task_categories:
- question-answering
language:
- uz
tags:
- uzbek
- linguistics
pretty_name: uzlib
size_categories:
- 1K<n<10K
---
# Uzbek Linguistic Benchmark (UzLiB)

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description
- **Homepage:** [tilmoch.ai](https://tilmoch.ai/uzlib-ozbekcha-lingvistik-benchmark)
- **Repository:** [https://github.com/tahrirchi/uzlib](https://github.com/tahrirchi/uzlib)
- **Point of Contact:** [a.shopulatov@tilmoch.ai](mailto:a.shopulatov@tilmoch.ai)
- **Size of downloaded dataset files:** 144 kB
- **Size of the generated dataset:** 144 kB
- **Total amount of disk used:** 331 kB

## Dataset Description

**UzLiB (Uzbek Linguistic Benchmark)** is the first comprehensive multiple-choice question benchmark designed to evaluate the linguistic understanding and capabilities of Large Language Models (LLMs) in the Uzbek language. It assesses how well models grasp correct Uzbek forms, usage, meanings, and contextual nuances.

For more detailed background on the motivation, creation process, and initial findings, please refer to our [blog post (in Uzbek)](https://tilmoch.ai/uzlib-ozbekcha-lingvistik-benchmark). You can find the evaluation scripts and leaderboard at the [GitHub repository](https://github.com/tahrirchi/uzlib).

## How to Use

To load and use the dataset:

```python
from datasets import load_dataset

uzlib = load_dataset("tahrirchi/uzlib")
uzlib
```

## Dataset Structure

The dataset consists of multiple-choice questions, each with four options and a single correct answer.

**Example Data Point:**
```json
{
  "id": "CW1242",
  "question": "Berilgan variantlar orasida qaysi biri to‘g‘ri yozilgan?",
  "option_a": "Samolyod",
  "option_b": "Samalyot",
  "option_c": "Samalyod",
  "option_d": "Samolyot",
  "answer": "D",
  "type": "correct_word"
}
```

### Data Fields

-   `id` (`string`): Unique identifier for the question.
-   `question` (`string`): The text of the question.
-   `option_a` (`string`): Answer option A.
-   `option_b` (`string`): Answer option B.
-   `option_c` (`string`): Answer option C.
-   `option_d` (`string`): Answer option D.
-   `answer` (`string`): The correct option label (`A`, `B`, `C`, or `D`).
-   `type` (`string`): Category of the question. One of:
    -   `correct_word`: Correct spelling or word form.
    -   `meaning`: Definition of words or phrases.
    -   `meaning_in_context`: Word usage in specific contexts.
    -   `fill_in`: Filling blanks in sentences.

### Data Splits / Configurations

The benchmark contains 1861 questions, categorized as follows:

| Category / Split Name | Number of Examples |
|:----------------------|-------------------:|
| `correct_word`        | 1501               |
| `meaning`             | 236                |
| `meaning_in_context`  | 72                 |
| `fill_in`             | 52                 |
| **Total**             | **1861**           |

## Dataset Creation

The questions were sourced from quizzes administered on popular Telegram channels dedicated to Uzbek language expertise:
-   [Orif Tolib](https://t.me/oriftolib)
-   [Тўғри ёзамиз — мутахассис блоги](https://t.me/xatoliklar)
-   [Tahrir.uz📝](https://t.me/tahrir_uz)
-   [Tahrirchi | Tilmoch](https://t.me/tahrirchi_uz)

**Curation Process:**
1.  **Collection:** Gathering quizzes from the specified Telegram channels.
2.  **Verification:** Manually identifying and confirming the correct answer for each quiz question, as this is not directly provided by the Telegram quiz export.
3.  **Filtering:** Removing duplicate or unsuitable questions.
4.  **Categorization:** Assigning each question to one of the four types (`correct_word`, `meaning`, `meaning_in_context`, and `fill_in`).
5.  **Standardization:** Ensuring every question has exactly four multiple-choice options (A, B, C, D). This involved manually creating distractor options for questions originally having fewer choices, standardizing the random guess probability to 25%.
6.  **Transliteration:** Converting all text to the Uzbek Latin script.
7.  **Shuffling:** Randomizing the order of answer options (A, B, C, D) for each question.

## Citation Information

If you use UzLiB in your research or application, please cite it as follows:

```bibtex
@misc{Shopulatov2025UzLiB,
      title={{UzLiB: A Benchmark for Evaluating LLMs on Uzbek Linguistics}},
      author={Abror Shopulatov},
      year={2025},
      howpublished={\url{https://huggingface.co/datasets/tahrirchi/uzlib}},
      note={Accessed: YYYY-MM-DD} % Please update with the date you accessed the dataset
}
```

## Contact

For inquiries regarding the dataset, please contact [a.shopulatov@tilmoch.ai](mailto:a.shopulatov@tilmoch.ai). For issues related to the evaluation code, please refer to the [GitHub repository](https://github.com/tahrirchi/uzlib).