Skip to main content
SpringerLink
Log in

Development of Web Service for Japanese Text Triplification

  • Published:
New Generation Computing Aims and scope Submit manuscript

Abstract

Linked Open Data (LOD) is recently attracting attention as a vast amount of distributed knowledge base on the Web. Thus, semi-structured data such as tables and hierarchical data in several domains have been triplified to the LOD. Moreover, triplification of unstructured data such as text and sensor data is actively studied in the research area. We thus developed a Web API for extracting triples from natural sentences, which is useful for the promotion of the LOD. In this paper, we first describe the service specification, its technical background, and the evaluation of the current extraction accuracy, and then introduce several use cases of the service. Although this service adopts a novel combination of a method using ontology-based rules and a machine learning method using Conditional Random Field based on a probability distribution, the main contributions are in the practical aspect, that is, mashup of several natural language processing (NLP) techniques for the text triplification, and its deployment as a public Web API, so that non-experts of NLP can easily use it.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Usbeck, R., Ngomo, A. C. N., Roder, M., Gerber, D., Coelho, S. A., Auer, S. and Both, A., “AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data,” Proc. of 13th International Semantic Web Conference (ISWC 2014), pp. 457–471, 2014.

  2. Fillmore, C. J., “The Case for Case,” Universals in Linguistic Theory, pp. 1–88, 1968.

  3. Mooney, R. J., CS 388: Natural Language Processing, 2014, http://www.cs.utexas.edu/~mooney/cs388/slides/srl.ppt.

  4. Sammons, M., Semantic Parsing (Semantic Role Labeling), 2014, http://cogcomp.cs.illinois.edu/page/project_view/7.

  5. Yoshikawa, K., Asahara, M., Matumoto, Y., “Jointly Extracting Japanese Predicate-Argument Structure Relation with Markov Logic,” Journal of Natural Language Processing, 20, 2, pp. 251–271, 2013. (in Japanese)

  6. Radinsky, K., Davidovich, S. and Markovitch, S., “Learning Causality for News Events Prediction,” Proc. of 21st World Wide Web Conference (WWW 2012), pp. 909–918, 2012.

  7. Kawamura, T., Nagano, S., Ohsuga, A., “Deployment of Semantic Analysis to Call Center,” Proc. of 13th International Semantic Web Conference (ISWC 2014), Industry Track, 2014.

  8. Lee, T. B., Linked Data, 2006, http://www.w3.org/DesignIssues/LinkedData.html.

  9. Sammons, M., Semantic Role Labeling Demo, 2014, http://cogcomp.cs.illinois.edu/page/demo_view/srl.

  10. Lafferty, J. D., McCallum, A., Pereira, F. C. N., “Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data,” Proc. of 18th International Conference on Machine Learning (ICML 2001), pp. 282–289, 2001.

  11. Nguyen, T. M., Kawamura, T., Tahara, Y., Ohsuga, A., “Building a Time Series Action Network for Earthquake Disaster,” Proc. of 4th ACM International Conference on Agents and Artificial Intelligence (ICAART 2012), pp. 100–108, 2012.

  12. Kawamura, T., Koshikawa, K., Nakagawa, H., Sei, Y., Tahara, Y., Ohsuga, A., “Proposal of Social-Mass Media Triplification and its Use Case,” IEICE Transactions on Information and Systems, J96-D, 12, pp. 2987–2999, 2013. (in Japanese)

  13. Wang M., Kawamura T., Sei Y., Nakagawa H., Tahara Y., Ohsuga A.: “Music Recommender Adapting Implicit Context Using ‘renso’ Relation among Linked Data,”. Journal of Information Processing 22(2), 279–288 (2014)

    Article  Google Scholar 

  14. Yoko, R., Kawamura, T., Sei, Y., Tahara, Y., Ohsuga, A., “News Curation Service using Semantic Graph Matching,” Proc. of 9th International Conference on Advances in Semantic Processing (SEMAPRO 2015), pp. 25–31, 2015.

  15. Terence, P., Events in the Semantics of English, MIT Press, 1990.

  16. Gildea D., Jurafsky D.: “Automatic Labeling of Semantic Roles,”. Computational Linguistics 28(3), 245–288 (2002)

    Article  Google Scholar 

  17. Collobert R., Weston J., Bottou L., Karlen M., Kavukcuoglu K., Kuksa P.: “Natural Language Processing (Almost) from Scratch,”. Journal of Machine Learning Research (JMLR) 12, 2461–2505 (2011)

    MathSciNet  MATH  Google Scholar 

  18. Collobert, R., “Deep Learning for Efficient Discriminative Parsing,” Proc. of 14th International Conference on Artificial Intelligence and Statistics (AIS-TATS), pp. 224–232, 2011.

  19. Liu, X., Li, K., Han, B., Zhou, M., Jiang, L., Xiong, Z. and Huang, C., “Semantic role labeling for news tweets,” Proc. of 23rd International Conference on Computational Linguistics (Coling 2010), pp. 698–706, 2010.

  20. Liu, X., Li, K., Zhou, M. and Xiong, Z., “Collective semantic role labeling for tweets with clustering,” Proc. of 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 1832–1837, 2011.

  21. Meza-Ruiz, I. and Riedel, S., “Jointly identifying predicates, arguments and senses using markov logic,” Proc. of 2009 Annual Conference of the North American Chapter of the ACL (NAACL 2009), pp. 155–163, 2009.

  22. Kawamura, T., Nagano, S., Ohsuga, A., “Literal Node Matching based on Image Features toward Linked Data Integration,” Proc. of 2014 IEEE/WIC/ACM International Conference on Active Media Technology (AMT 2014), pp. 174–186, 2014.

Download references

Author information

Authors and Affiliations

  1. Department of Information Planning, Japan Science and Technology Agency, Chiyoda-ku, 102-8666, Japan

    Takahiro Kawamura

  2. Graduate School of Information Systems, University of Electro-Communications, Chofu-shi, 182-8585, Japan

    Akihiko Ohsuga

Authors
  1. Takahiro Kawamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akihiko Ohsuga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Takahiro Kawamura.

Additional information

In association with The Japanese Society for Artificial Intelligence

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kawamura, T., Ohsuga, A. Development of Web Service for Japanese Text Triplification. New Gener. Comput. 34, 307–322 (2016). https://doi.org/10.1007/s00354-016-0401-0

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00354-016-0401-0

Keywords

Search

Navigation