Skip to main content

Pini Language and PiniTree Ontology Editor: Annotation and Verbalisation for Atomised Journalism

  • 443 Accesses

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12124)

Abstract

We present a new ontology language Pini and the PiniTree ontology editor supporting it. Despite Pini language bearing lot of similarities with RDF, UML class diagrams, Property Graphs and their frontends like Google Knowledge Graph and Protégé, it is a more expressive language enabling FrameNet-style natural language annotation for Atomised journalism use case.

Keywords

  • Ontology languages and editors
  • Natural language processing

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-62327-2_6
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-62327-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

References

  1. Rhianne, J., Bronwyn Jones, J.: Atomising the news: the (in)flexibility of structured journalism. Digital Journal. 7(8), 1157–1179 (2019)

    Google Scholar 

  2. Rumbaugh, J., Jacobson, I., Booch, G.: The Unified Modeling Language Reference Manual, 2nd edn. Addison-Wesley, Boston (2005)

    Google Scholar 

  3. Resource Description Framework (RDF). http://www.w3.org/RDF. Accessed 05 May 2020

  4. Robinson, I., Webber, J., Eifrem, E.: Graph Databases. O’Reilly Media, Sebastopol (2013)

    Google Scholar 

  5. Google Knowledge Graph. https://developers.google.com/knowledge-graph. Accessed 05 May 2020

  6. Fillmore, C.J., Johnson, C.R., Petruck, M.R.L.: Background to FrameNet. Int. J. Lexicogr. 16, 235–250 (2003)

    CrossRef  Google Scholar 

  7. Barzdins, G., Gosko, D., Rituma, L., Paikens, P.: Using C5.0 and exhaustive search for boosting frame-semantic parsing accuracy. In: LREC2014, pp. 4476–4482 (2014)

    Google Scholar 

  8. Hartig, O.: Reconciliation of RDF* and Property Graphs. arXiv:1409.3288 (2014)

  9. FreeBase graphd Repository. https://github.com/google/graphd. Accessed 05 May 2020

  10. Dhingra, B., et al.: Differentiable reasoning over a virtual knowledge base. In: ICLR (2020)

    Google Scholar 

Download references

Acknowledgments

The research leading to these results has received funding also from the ERDF project 1.1.1.1/18/A/045 at IMCS, University of Latvia, and from the project “Competence Centre of Information and Communication Technologies” of EU Structural funds, No. 1.2.1.1/18/A/003, Research No. 2.4 “Platform for the semantically structured information extraction from the massive Latvian news archive”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guntis Barzdins .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Barzdins, G. et al. (2020). Pini Language and PiniTree Ontology Editor: Annotation and Verbalisation for Atomised Journalism. In: , et al. The Semantic Web: ESWC 2020 Satellite Events. ESWC 2020. Lecture Notes in Computer Science(), vol 12124. Springer, Cham. https://doi.org/10.1007/978-3-030-62327-2_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62327-2_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62326-5

  • Online ISBN: 978-3-030-62327-2

  • eBook Packages: Computer ScienceComputer Science (R0)