Upload README.md

README.md

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+# Dataset Card for HVU_QA
+
+**HVU_QA** is an open-source Vietnamese Question–Context–Answer (QCA) corpus and supporting tools for building FAQ-style question generation systems in low-resource languages.  
+The dataset was created using a fully automated pipeline that combines **web crawling from trustworthy sources, semantic tag-based extraction, and AI-assisted filtering** to ensure high factual accuracy.
+
+---
+
+## Dataset Summary
+
+- **Language:** Vietnamese  
+- **Format:** SQuAD-style JSON  
+- **Total samples:** 30,000 QCA triples (full corpus released)  
+- **Domains covered:** Social services, labor law, administrative processes, and other public service topics  
+
+Each entry in the dataset has the following structure:
+- **Question:** Generated or extracted question  
+- **Context:** Supporting text passage from which the answer is derived  
+- **Answer:** Answer span within the context  
+
+---
+
+## Supported Tasks and Benchmarks
+
+- **Question Generation (QG)**  
+- **Question Answering (QA)**  
+- **FAQ-style dialogue systems**  
+
+A fine-tuned `VietAI/vit5-base` model trained on HVU_QA achieved:  
+- **BLEU:** 90.61  
+- **Semantic similarity:** 97.0% (cosine similarity ≥ 0.8)  
+- **Human evaluation:**  
+  - Grammaticality: 4.58 / 5  
+  - Usefulness: 4.29 / 5  
+
+---
+
+## Languages
+
+- **Vietnamese** (primary)  
+
+---
+
+## Dataset Structure
+
+### Data Fields
+
+Each sample contains:
+- `question`: A natural language question  
+- `context`: Supporting text passage  
+- `answer`: The extracted answer span  
+
+### Data Splits
+
+| Split | Size |
+|-------|------|
+| Train | 30,000 |
+
+---
+
+## Dataset Creation
+
+### Creation Pipeline
+
+The dataset was built using a 4-stage automated process:
+1. **Selecting relevant QA websites** from trusted sources  
+2. **Automated data crawling** to collect raw QA webpages  
+3. **Extraction via semantic tags** to obtain clean Q–C–A triples  
+4. **AI-assisted filtering** to remove noisy or factually inconsistent samples  
+
+---
+
+## Usage Example
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("DANGDOCAO/GeneratingQuestions")
+print(dataset["train"][0])
+```
+
+Example output:
+```json
+{
+  "question": "What type of coffee is famous in Vietnam?",
+  "context": "Iced milk coffee is a famous drink in Vietnam.",
+  "answer": "Iced milk coffee"
+}
+```
+
+---
+
+## Training & Fine-tuning
+
+To fine-tune a question generation model:
+
+```bash
+python fine_tune_qg.py
+```
+
+- Loads `30ktrain.json`  
+- Fine-tunes `VietAI/vit5-base`  
+- Saves model as `t5-viet-qg-finetuned/`  
+
+👉 Alternatively, you can use the pre-trained model provided here:  
+[Pre-trained model link](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions/tree/main)
+
+---
+
+## Question Generation Example
+
+```bash
+python generate_question.py
+```
+
+**Input passage:**
+```
+Iced milk coffee is a famous drink in Vietnam.
+```
+
+**Generated questions:**
+1. What type of coffee is famous in Vietnam?  
+2. Why is iced milk coffee popular?  
+3. What ingredients are included in iced milk coffee?  
+4. Where does iced milk coffee originate from?  
+5. How is Vietnamese iced milk coffee prepared?  
+
+---
+
+## Citation
+
+If you use **HVU_QA** in your research, please cite:
+
+```bibtex
+@inproceedings{nguyen2025hvuqa,
+  title={A Method to Build QA Corpora for Low-Resource Languages},
+  author={Ha Nguyen-Tien and Phuc Le-Hong and Dang Do-Cao and Cuong Nguyen-Hung and Chung Mai-Van},
+  booktitle={Proceedings of the International Conference on Knowledge and Systems Engineering (KSE)},
+  year={2025}
+}
+```
+
+---
+
+## License
+
+This dataset is released for **research purposes only** under the **CC BY-NC-SA 4.0 license**.