Skip to main content
SpringerLink
Log in

Fact Checking from Natural Text with Probabilistic Soft Logic

  • Conference paper
  • First Online:
Book cover Advances in Intelligent Data Analysis XVII (IDA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11191))

Included in the following conference series:

  • 1313 Accesses

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).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Royal Family tree and line of succession: http://www.bbc.co.uk/news/uk-23272491.

References

  1. Ba, M.L., Berti-Equille, L., Shah, K., Hammady, H.M.: Vera: A platform for veracity estimation over web data. In: Proceedings of the 25th International Conference Companion on World Wide Web, International World Wide Web Conferences Steering Committee, pp. 159–162 (2016)

    Google Scholar 

  2. Bach, S., Huang, B., London, B., Getoor, L.: Hinge-loss Markov random fields: convex inference for structured prediction. arXiv preprint arXiv:1309.6813 (2013)

  3. Cartwright, D., Harary, F.: Structural balance: a generalization of Heider’s theory. Psychol. Rev. 63(5), 277 (1956)

    Article  Google Scholar 

  4. Cunningham, H., Wilks, Y., Gaizauskas, R.J.: Gate: a general architecture for text engineering. In: Proceedings of the 16th Conference on Computational Linguistics, vol. 2, pp. 1057–1060. Association for Computational Linguistics (1996)

    Google Scholar 

  5. Flaounas, I., Lansdall-Welfare, T., Antonakaki, P., Cristianini, N.: The anatomy of a modular system for media content analysis. arXiv preprint arXiv:1402.6208 (2014)

  6. Hassan, N., et al.: The quest to automate fact-checking. World (2015)

    Google Scholar 

  7. Hassan, N., et al.: Claimbuster: the first-ever end-to-end fact-checking system. Proc. VLDB Endow. 10(12), 1945–1948 (2017)

    Article  Google Scholar 

  8. Jo, S., Trummer, I., Yu, W., Liu, D., Mehta, N.: The factchecker: verifying text summaries of relational data sets. arXiv preprint arXiv:1804.07686 (2018)

  9. Kimmig, A., Bach, S., Broecheler, M., Huang, B., Getoor, L.: A short introduction to probabilistic soft logic. In: Proceedings of the NIPS Workshop on Probabilistic Programming: Foundations and Applications, pp. 1–4 (2012)

    Google Scholar 

  10. Leblay, J.: A declarative approach to data-driven fact checking. In: AAAI, pp. 147–153 (2017)

    Google Scholar 

  11. Leblay, J., Chen, W., Lynden, S.: Exploring the veracity of online claims with backdrop. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp. 2491–2494. ACM (2017)

    Google Scholar 

  12. Patwari, A., Goldwasser, D., Bagchi, S.: Tathya: A multi-classifier system for detecting check-worthy statements in political debates. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp. 2259–2262. ACM (2017)

    Google Scholar 

  13. Soon, W.M., Ng, H.T., Lim, D.C.Y.: A machine learning approach to coreference resolution of noun phrases. Comput. Linguist. 27(4), 521–544 (2001)

    Article  Google Scholar 

  14. Sudhahar, S., De Fazio, G., Franzosi, R., Cristianini, N.: Network analysis of narrative content in large corpora. Nat. Lang. Eng. 21(1), 81–112 (2015)

    Article  Google Scholar 

  15. Thorne, J., Vlachos, A.: An extensible framework for verification of numerical claims. In: Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp. 37–40. Association for Computational Linguistics (2017)

    Google Scholar 

  16. Vlachos, A., Riedel, S.: Identification and verification of simple claims about statistical properties. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 2596–2601. Association for Computational Linguistics (2015)

    Google Scholar 

  17. Wilson, E.B.: Probable inference, the law of succession, and statistical inference. J. Am. Stat. Assoc. 22(158), 209–212 (1927)

    Article  Google Scholar 

  18. Wu, Y., et al.: iCheck: computationally combating lies, d-ned lies, and statistics. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, pp. 1063–1066. ACM (2014)

    Google Scholar 

Download references

Acknowledgements

NC and SS were supported by ERC, NB was supported by a grant from KSU, Saudi Arabia.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bristol, Bristol, UK

    Nouf Bindris, Saatviga Sudhahar & Nello Cristianini

Authors
  1. Nouf Bindris
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saatviga Sudhahar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nello Cristianini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nouf Bindris .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Wouter Duivesteijn

  2. Department of Information and Computing Sciences, University Utrecht, Utrecht, The Netherlands

    Arno Siebes

  3. University of Helsinki, Helsinki, Finland

    Antti Ukkonen

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bindris, N., Sudhahar, S., Cristianini, N. (2018). Fact Checking from Natural Text with Probabilistic Soft Logic. In: Duivesteijn, W., Siebes, A., Ukkonen, A. (eds) Advances in Intelligent Data Analysis XVII. IDA 2018. Lecture Notes in Computer Science(), vol 11191. Springer, Cham. https://doi.org/10.1007/978-3-030-01768-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-01768-2_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01767-5

  • Online ISBN: 978-3-030-01768-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation