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--- |
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license: mit |
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task_categories: |
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- question-answering |
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- text-generation |
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- table-question-answering |
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- sentence-similarity |
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- feature-extraction |
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language: |
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- vi |
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tags: |
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- question-generation |
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- nlp |
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- faq |
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- low-resource |
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- code |
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pretty_name: HVU_QA |
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size_categories: |
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- 10K<n<100K |
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--- |
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# HVU_QA |
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**HVU_QA** is an open-source Vietnamese Question–Context–Answer (QCA) corpus, accompanied by supporting tools, created to facilitate the development of FAQ-style question generation and question answering systems, particularly for low-resource language settings. The dataset is developed by a research team at Hung Vuong University, Phu Tho, Vietnam, led by Dr. Ha Nguyen, Deputy Head of the Department of Engineering Technology. HVU_QA was constructed using a fully automated data-building pipeline that combines web crawling from reliable sources, semantic tag-based extraction, and AI-assisted filtering, helping ensure high factual accuracy, consistent structure, and practical usability for real-world applications. |
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## 📋 Dataset Description |
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- **Language:** Vietnamese |
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- **Format:** SQuAD-style JSON |
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- **Total samples:** 39,000 QCA triples (full corpus released) |
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- **Domains covered:** Social services, labor law, administrative processes, and other public service topics. |
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- **Structure of each sample:** |
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- **Question:** Generated or extracted question |
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- **Context:** Supporting text passage from which the answer is derived |
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- **Answer:** Answer span within the context |
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## ⚙️ Creation Pipeline |
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The dataset was built using a 4-stage automated process: |
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1. **Selecting relevant QA websites** from trusted sources. |
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2. **Automated data crawling** to collect raw QA webpages. |
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3. **Extraction via semantic tags** to obtain clean Question–Context–Answer triples. |
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4. **AI-assisted filtering** to remove noisy or factually inconsistent samples. |
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## 📊 Quality Evaluation |
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A fine-tuned `vit5-base` model trained on HVU_QA achieved: |
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| Metric | Score | |
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|-------------------------|----------------| |
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| BLEU | 89.1 | |
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| Semantic similarity | 91.5% (cos ≥ 0.8) | |
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| Human grammar score | 4.58 / 5 | |
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| Human usefulness score | 4.29 / 5 | |
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These results confirm that HVU_QA is a high-quality resource for developing robust FAQ-style question generation models. |
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## 📁 Dataset Structure |
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``` |
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.HVU_QA |
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├── t5-viet-qg-finetuned/ |
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├── fine_tune_qg.py |
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├── generate_question.py |
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├── 39k_train.json |
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└── README.md |
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``` |
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## 📁 Vietnamese Question Generation Tool |
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## 🛠️ Requirements |
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* Python 3.8+ |
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* PyTorch >= 1.9 |
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* Transformers >= 4.30 |
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* scikit-learn |
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### 📦 Install Required Libraries |
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```bash |
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pip install datasets transformers sentencepiece safetensors accelerate evaluate sacrebleu rouge-score nltk scikit-learn |
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``` |
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*(Install PyTorch separately from [pytorch.org](https://pytorch.org) if not installed yet.)* |
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### 📥 Load Dataset from Hugging Face Hub |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("DANGDOCAO/GeneratingQuestions", split="train") |
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print(ds[0]) |
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``` |
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## 📚 Usage |
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* Train and evaluate a question generation model. |
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* Develop Vietnamese NLP tools. |
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* Conduct linguistic research. |
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### 🔹 Fine-tuning |
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```bash |
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python fine_tune_qg.py |
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``` |
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This will: |
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1. Load the dataset from `39k_train.json`. |
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2. Fine-tune `VietAI/vit5-base`. |
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3. Save the trained model into `t5-viet-qg-finetuned/`. |
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*(Or download the pre-trained model: [t5-viet-qg-finetuned](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions/tree/main).)* |
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### 🔹 Generating Questions |
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```bash |
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python generate_question.py |
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``` |
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**Example:** |
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``` |
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Input passage: |
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Cà phê sữa đá là một loại đồ uống nổi tiếng ở Việt Nam |
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(Iced milk coffee is a famous drink in Vietnam) |
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Number of questions: 5 |
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``` |
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**Output:** |
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``` |
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1. Loại cà phê nào nổi tiếng ở Việt Nam? |
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(What type of coffee is famous in Vietnam?) |
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2. Tại sao cà phê sữa đá lại phổ biến? |
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(Why is iced milk coffee popular?) |
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3. Cà phê sữa đá bao gồm những nguyên liệu gì? |
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(What ingredients are included in iced milk coffee?) |
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4. Cà phê sữa đá có nguồn gốc từ đâu? |
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(Where does iced milk coffee originate from?) |
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5. Cà phê sữa đá Việt Nam được pha chế như thế nào? |
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(How is Vietnamese iced milk coffee prepared?) |
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``` |
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**You can adjust** in `generate_question.py`: |
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- `top_k`, `top_p`, `temperature`, `no_repeat_ngram_size`, `repetition_penalty` |
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## 📌 Citation |
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If you use **HVU_QA** in your research, please cite: |
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```bibtex |
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@inproceedings{nguyen2025method, |
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author = {Ha Nguyen and Phuc Le and Dang Do and Cuong Nguyen and Chung Mai}, |
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title = {A Method for Building QA Corpora for Low-Resource Languages}, |
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booktitle = {Proceedings of the 2025 International Symposium on Information and Communication Technology (SOICT 2025)}, |
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year = {2025}, |
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publisher = {Springer}, |
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series = {Communications in Computer and Information Science (CCIS)}, |
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address = {Nha Trang, Vietnam}, |
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note = {To appear} |
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} |
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``` |
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## ❤️ Support / Funding |
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If you find **HVU_QA** useful, please consider supporting our work. |
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Your contributions help us maintain the dataset, improve quality, and release new versions (cleaning, expansion, benchmarks, and tools). |
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### 🇻🇳 Donate via VietQR (scan to support) |
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This **VietQR / NAPAS 247** code can be scanned by Vietnamese banking apps and some international payment apps that support QR bank transfers. |
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<img src="QRtk.jpg" alt="VietQR Support" width="320"/> |
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**Bank:** VietinBank (Vietnam) |
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**Account name:** NGUYEN TIEN HA |
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**Account number:** 103004492490 |
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**Branch:** VietinBank CN PHU THO - HOI SO |
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### 🌍 International Support (Quick card payment) |
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If you are outside Vietnam, you can support this project via **Buy Me a Coffee** |
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(no PayPal account needed — pay directly with a credit/debit card): |
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- BuyMeACoffee: https://buymeacoffee.com/hanguyen0408 |
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### 🌍 International Support (PayPal) |
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If you prefer PayPal, you can also support us here: |
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- PayPal.me: https://paypal.me/HaNguyen0408 |
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### ✨ Other ways to support |
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- ⭐ Star this repository / dataset on Hugging Face |
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- 📌 Cite our paper if you use it in your research |
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- 🐛 Open issues / pull requests to improve the dataset and tools |
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- |
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📬 Contact / Maintainers |
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For questions, feedback, collaborations, or issue reports related to HVU_QA, please contact: |
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Dr. Ha Nguyen (Project Lead) |
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Hung Vuong University, Phu Tho, Vietnam |
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Email: nguyentienha@hvu.edu.vn |