# Analysis of Wikipedia-based Corpora for Question Answering

Source: [Analysis of Wikipedia-based Corpora for Question Answering](<https://www.sota2.com/research/paper/68fa640b1e209131cea02458>)

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

Data updated: 2025-10-25T20:55:10.976Z

Authors: Tomasz Jurczyk, Amit Deshmane, Jinho D. Choi

Published: 2018-01-06T19:28:15.000Z

## Abstract

This paper gives comprehensive analyses of corpora based on Wikipedia for several tasks in question answering. Four recent corpora are collected,WikiQA, SelQA, SQuAD, and InfoQA, and first analyzed intrinsically by contextual similarities, question types, and answer categories. These corpora are then analyzed extrinsically by three question answering tasks, answer retrieval, selection, and triggering. An indexing-based method for the creation of a silver-standard dataset for answer retrieval using the entire Wikipedia is also presented. Our analysis shows the uniqueness of these corpora and suggests a better use of them for statistical question answering learning.

## 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/1801.02073>)

[PDF](<https://arxiv.org/pdf/1801.02073.pdf>)