# ParaQG: A System for Generating Questions and Answers from Paragraphs

arXiv: https://arxiv.org/abs/1909.01642 · HTML: https://mlsanity.com/paper/1909.01642/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Sep 2019.

## Built on by (most cited first, 2 of 2)

- [AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents](https://mlsanity.com/paper/2103.03820/) (2021)
- [An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers](https://mlsanity.com/paper/2112.01229/) (2021)

## Abstract (arXiv)

Generating syntactically and semantically valid and relevant questions from paragraphs is useful with many applications. Manual generation is a labour-intensive task, as it requires the reading, parsing and understanding of long passages of text. A number of question generation models based on sequence-to-sequence techniques have recently been proposed. Most of them generate questions from sentences only, and none of them is publicly available as an easy-to-use service. In this paper, we demonstrate ParaQG, a Web-based system for generating questions from sentences and paragraphs. ParaQG incorporates a number of novel functionalities to make the question generation process user-friendly. It provides an interactive interface for a user to select answers with visual insights on generation of questions. It also employs various faceted views to group similar questions as well as filtering techniques to eliminate unanswerable questions