Working Paper Review Version 1 This version is not peer-reviewed

Datasets for Machine Reading Comprehension: A Literature Review

Version 1 : Received: 5 October 2019 / Approved: 8 October 2019 / Online: 8 October 2019 (10:40:09 CEST)

A peer-reviewed article of this Preprint also exists.


Machine reading comprehension aims to teach machines to understand a text like a human, and is a new challenging direction in Artificial Intelligence. Datasets play an important role while describing or building an algorithm for machine reading comprehension. The type of answers we required from developed algorithm depends on datasets.The datasets are classified into two types, namely datasets with extractive answers and datasets with descriptive answers. This article summarize both datasets with an example of each type to get better insight of datasets in machine reading comprehension and which datasets to use depending the requirements.


Reading Comprehensio; Descriptive Answer; Extractive answer; Multiple-choice answers; Datasets


Computer Science and Mathematics, Data Structures, Algorithms and Complexity

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0

Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.