Fact Checking from Natural Text with Probabilistic Soft Logic

Nouf Bindris, Saatviga Sudhahar, Nello Cristianini

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

170 Downloads (Pure)

Abstract

We demonstrate a method to support fact-checking of statements found in natural text such as online news, encyclopedias or academic repositories, by detecting if they violate knowledge that is implicitly present in a reference corpus. The method combines the use of information extraction techniques with probabilistic reasoning, allowing for inferences to be performed starting from natural text. We present two case studies, one in the domain of verifying claims about family relations, the other about political relations. This allows us to contrast the case where ground truth is available about the relations and the rules that can be applied to them (families) with the case where neither relations nor rules are clear cut (politics).
Original languageEnglish
Title of host publicationAdvances in Intelligent Data Analysis XVII
Subtitle of host publication17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings
PublisherSpringer, Cham
Pages52-61
Number of pages10
ISBN (Electronic)9783030017682
ISBN (Print)9783030017675
DOIs
Publication statusPublished - 5 Oct 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11191
ISSN (Print)0302-9743

Keywords

  • Fact checking
  • Information extraction
  • Probabilistic soft logic

Cite this