Fact Checking from Natural Text with Probabilistic Soft Logic

Nouf Bindris; Saatviga Sudhahar; Nello Cristianini

doi:10.1007/978-3-030-01768-2_5

Fact Checking from Natural Text with Probabilistic Soft Logic

Nouf Bindris, Saatviga Sudhahar, Nello Cristianini

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

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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 language	English
Title of host publication	Advances in Intelligent Data Analysis XVII
Subtitle of host publication	17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings
Publisher	Springer, Cham
Pages	52-61
Number of pages	10
ISBN (Electronic)	9783030017682
ISBN (Print)	9783030017675
DOIs	https://doi.org/10.1007/978-3-030-01768-2_5
Publication status	Published - 5 Oct 2018

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11191
ISSN (Print)	0302-9743

Keywords

Fact checking
Information extraction
Probabilistic soft logic

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10.1007/978-3-030-01768-2_5

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Bindris, N., Sudhahar, S., & Cristianini, N. (2018). Fact Checking from Natural Text with Probabilistic Soft Logic. In Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings (pp. 52-61). (Lecture Notes in Computer Science; Vol. 11191). Springer, Cham. https://doi.org/10.1007/978-3-030-01768-2_5

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Bindris, N, Sudhahar, S & Cristianini, N 2018, Fact Checking from Natural Text with Probabilistic Soft Logic. in Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. Lecture Notes in Computer Science, vol. 11191, Springer, Cham, pp. 52-61. https://doi.org/10.1007/978-3-030-01768-2_5

Fact Checking from Natural Text with Probabilistic Soft Logic. / Bindris, Nouf; Sudhahar, Saatviga; Cristianini, Nello.
Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. Springer, Cham, 2018. p. 52-61 (Lecture Notes in Computer Science; Vol. 11191).

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

TY - GEN

T1 - Fact Checking from Natural Text with Probabilistic Soft Logic

AU - Bindris, Nouf

AU - Sudhahar, Saatviga

AU - Cristianini, Nello

PY - 2018/10/5

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N2 - 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).

AB - 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).

KW - Fact checking

KW - Information extraction

KW - Probabilistic soft logic

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DO - 10.1007/978-3-030-01768-2_5

M3 - Conference Contribution (Conference Proceeding)

SN - 9783030017675

T3 - Lecture Notes in Computer Science

SP - 52

EP - 61

BT - Advances in Intelligent Data Analysis XVII

PB - Springer, Cham

ER -

Fact Checking from Natural Text with Probabilistic Soft Logic

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