# Question Answering is a Format; When is it Useful?

Source: [Question Answering is a Format; When is it Useful?](<https://www.sota2.com/research/paper/68fa66741e209131cea1030d>)

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

Data updated: 2025-10-25T21:49:28.917Z

Authors: Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, Sewon Min

Published: 2019-09-25T05:16:15.000Z

## Abstract

Recent years have seen a dramatic expansion of tasks and datasets posed as question answering, from reading comprehension, semantic role labeling, and even machine translation, to image and video understanding. With this expansion, there are many differing views on the utility and definition of "question answering" itself. Some argue that its scope should be narrow, or broad, or that it is overused in datasets today. In this opinion piece, we argue that question answering should be considered a format which is sometimes useful for studying particular phenomena, not a phenomenon or task in itself. We discuss when a task is correctly described as question answering, and when a task is usefully posed as question answering, instead of using some other format.

## 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/1909.11291>)

[PDF](<https://arxiv.org/pdf/1909.11291.pdf>)