updating README

README.md

@@ -82,81 +82,106 @@ size_categories:
   - [Contributions](#contributions)
 
 ## Dataset Description
-- **Homepage:** [hf.co/datasets/murodbek/uzlib](https://huggingface.co/datasets/murodbek/uzlib)
-- **Repository:** [https://github.com/shopulatov/uzlib](https://github.com/shopulatov/uzlib)
-- **Point of Contact:** [ml.muhandis@gmail.com](mailto:ml.muhandis@gmail.com)
+- **Homepage:** [tilmoch.ai/index/uzlib-ozbek-lingvistik-benchmark](https://tilmoch.ai/index/uzlib-ozbek-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 Summary
+## 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.
 
-The Uzbek Linguistic Benchmark (UzLiB) is a benchmark with multiple-choice questions for evaluating linguistic abilities of Large Language Models (LLMs) in Uzbek language. 
+For more detailed background on the motivation, creation process, and initial findings, please refer to our [blog post (in Uzbek)](https://tilmoch.ai/index/uzlib-ozbek-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 dataset, run this script:
+To load and use the dataset:
 
 ```python
 from datasets import load_dataset
 
-uzlib = load_dataset("murodbek/uzlib")
+uzlib = load_dataset("tahrirchi/uzlib")
+uzlib
 ```
 
 ## Dataset Structure
 
-An example of `correct_word` looks as follows.
-
-```
-{'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'}
+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
-The data fields are the same among all splits.
 
-- `id`: a `string` feature to indicate id of the given question.
-- `question`: a `string` feature to question.
-- `option_a`: a `string` feature to indicate answer option A.
-- `option_b`: a `string` feature to indicate answer option B.
-- `option_c`: a `string` feature to indicate answer option C.
-- `option_d`: a `string` feature to indicate answer option D.
-- `answer`: a `string` feature to indicate the correct answer. One of `A`, `B`, `C` or `D`.
-- `type`: a `string` feature to indicate the type of the question. One of `correct_word`, `meaning`, `meaning_in_context` or `fill_in`. 
+-   `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**           |
 
-### Data Splits
-
-### Data Splits
+## Dataset Creation
 
-| split_name      |num_examples|
-|-----------------|-----------:|
-| correct_word    | 1501    |
-| meaning    | 236    |
-| meaning_in_context    | 72    |
-| fill_in  | 52     |
-| **all**  | **1861**     |
+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)
 
-## Dataset Creation
+**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.
 
-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. 
+## Citation Information
 
+If you use UzLiB in your research or application, please cite it as follows:
 
-### Citation Information
-```
+```bibtex
 @misc{Shopulatov2025UzLiB,
-      title={UzLiB: A benchmark for evaluating Uzbek linguistics}, 
+      title={{UzLiB: A Benchmark for Evaluating LLMs on Uzbek Linguistics}},
       author={Abror Shopulatov},
-      year={2025}
-      url={https://huggingface.co/datasets/murodbek/uzlib},
-      note={Accessed: 2025-02-18}, % change this date
-      urldate   = {2025-02-18}} % change this date
+      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 any questions or issues related to the dataset or code, please contact [ml.muhandis@gmail.com](mailto:ml.muhandis@gmail.com).
+## 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).