| # punctuation_restoration | |
| ## Dataset Summary | |
| This dataset is designed for **instruction fine-tuning** of large language models (LLMs), especially for the **Qwen3** family, to perform **punctuation restoration** on Mandarin Chinese text. | |
| It is derived from the [`AWeirdDev/zh-tw-articles-6k`](https://huggingface.co/datasets/AWeirdDev/zh-tw-articles-6k) dataset. The `context` field is processed to create input-output pairs in the Qwen3-style message format. | |
| - 🔧 **User message**: A cleaned version of the article with all punctuation removed, spaces added where punctuation was, and an instruction prefix. | |
| - ✍️ **Assistant message**: The original article with punctuation. | |
| - 🧠 **Use Case**: Fine-tuning Qwen3 or similar chat-style LLMs to restore punctuation from flat text. | |
| ## Format | |
| Each sample in the dataset follows this structure: | |
| ```json | |
| { | |
| "messages": [ | |
| { | |
| "role": "user", | |
| "content": "Your task is to restore the punctuations of this article:\nZhe li shi yi ge mei you biao dian de wen zhang ..." | |
| }, | |
| { | |
| "role": "assistant", | |
| "content": "這裡是一個沒有標點或者標點不全的文章，請你恢復正確的標點符號。" | |
| } | |
| ] | |
| } |