--- language: - ar license: apache-2.0 size_categories: - n<1K task_categories: - multiple-choice pretty_name: 'CIDAR-MCQ-100 ' dataset_info: features: - name: Question dtype: string - name: A dtype: string - name: B dtype: string - name: C dtype: string - name: D dtype: string - name: answer dtype: string splits: - name: test num_bytes: 18899 num_examples: 100 download_size: 13287 dataset_size: 18899 configs: - config_name: default data_files: - split: test path: data/test-* --- # Dataset Card for "CIDAR-MCQ-100" # CIDAR-MCQ-100 CIDAR-MCQ-100 contains **100** multiple-choice questions and answers about the Arabic culture. ## 📚 Datasets Summary
Name Explanation
CIDAR 10,000 instructions and responses in Arabic
CIDAR-EVAL-100 100 instructions to evaluate LLMs on cultural relevance
CIDAR-MCQ-100 100 Multiple choice questions and answers to evaluate LLMs on cultural relevance
| Category | CIDAR-EVAL-100 | CIDAR-MCQ-100| |----------|:-------------:|:------:| |Food&Drinks | 14 | 8 | |Names | 14 | 8 | |Animals | 2 | 4 | |Language | 10 | 20 | |Jokes&Puzzles | 3 | 7 | |Religion | 5 | 10 | |Business | 6 | 7 | |Cloths | 4 | 5 | |Science | 3 | 4 | |Sports&Games | 4 | 2 | |Tradition | 4 | 10 | |Weather | 4 | 2 | |Geography | 7 | 8 | |General | 4 | 3 | |Fonts | 5 | 2 | |Literature | 10 | 2 | |Plants | 3 | 0 | Total | 100 | 100 |
## 📋 Dataset Structure - `Question(str)`: Question about the Arabic culture. - `A(str)`: First choice. - `B(str)`: Second choice. - `C(str)`: Third choice. - `D(str)`: Fourth choice. - `answer(str)`: The correct choice from A,B,C, and D. ## 📁 Loading The Dataset You can download the dataset directly from HuggingFace or use the following code: ```python from datasets import load_dataset cidar = load_dataset('arbml/CIDAR-MCQ-100') ``` ## 📄 Sample From The Dataset: **Question**: حدد حيوان مشهور في المنطقة **A**: الجمل **B**: اللاما **C**: الكانغرو **D**: الدب القطبي **answer**: A ## 🔑 License The dataset is licensed under **Apache-2.0**. [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0). ## Citation ``` @misc{alyafeai2024cidar, title={{CIDAR: Culturally Relevant Instruction Dataset For Arabic}}, author={Zaid Alyafeai and Khalid Almubarak and Ahmed Ashraf and Deema Alnuhait and Saied Alshahrani and Gubran A. Q. Abdulrahman and Gamil Ahmed and Qais Gawah and Zead Saleh and Mustafa Ghaleb and Yousef Ali and Maged S. Al-Shaibani}, year={2024}, eprint={2402.03177}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```