# AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents

Source: [AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents](<https://www.sota2.com/research/paper/68fa696e1e209131cea21fd0>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:46.650Z

Authors: Melissa Roemmele, Deep Sidhpura, Steve DeNeefe, Ling Tsou

Published: 2021-03-05T17:36:04.000Z

## Abstract

One strategy for facilitating reading comprehension is to present information in a question-and-answer format. We demo a system that integrates the tasks of question answering (QA) and question generation (QG) in order to produce Q&A items that convey the content of multi-paragraph documents. We report some experiments for QA and QG that yield improvements on both tasks, and assess how they interact to produce a list of Q&A items for a text. The demo is accessible at qna.sdl.com.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2103.03820>)

[PDF](<https://arxiv.org/pdf/2103.03820.pdf>)