QnA Academic Chatbot

The dataset is derived from university academic handbooks, which include information on academic policies, administrative procedures, and student services. It is highly relevant for building generative chatbots in the context of academic services.
The dataset supports fine-tuning of Large Language Models (LLM) that enable fine-tuning large language models (such as GPT or BERT) to understand and generate responses according to the academic context.
Educational institutions can use this dataset to develop responsive and efficient self-service systems for students and staff.

Data acquisition.
The contents of the Academic Guidebook are summarized and produce 18 lines of question-answer (Q&A) pairs. The Q&A pairs are then paraphrased with the following details:
- Each question (Q) produces 10 paraphrased sentences (1 original sentence + 10 paraphrases)
- Each answer (A) produces 5 paraphrased sentences (1 original sentence + 5 paraphrases)
The dataset is converted into CSV format with question-answer (Q&A) pair structure and multi-turn conversation scenarios.