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Semantic Web Evaluation Challenge

SemWebEval 2018: Semantic Web Challenges pp 69–75Cite as

The Scalable Question Answering Over Linked Data (SQA) Challenge 2018

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 927))

Abstract

Question answering (QA) systems, which source answers to natural language questions from Semantic Web data, have recently shifted from the research realm to become commercially viable products. Increasing investments have refined an interaction paradigm that allows end users to profit from the expressive power of Semantic Web standards, while at the same time hiding their complexity behind intuitive and easy-to-use interfaces. Not surprisingly, after the first excitement we did not witness a cooling-down phenomenon: regular interactions with question answering systems have become more and more natural. As consumers expectations around the capabilities of systems able to answer questions formulated in natural language keep growing, so is the availability of such systems in various settings, devices and languages. Increasing usage in real (non-experimental) settings have boosted the demand for resilient systems, which can cope with high volume demand.

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Notes

  1. 1.

    http://www.sc.cit-ec.uni-bielefeld.de/qald/.

  2. 2.

    https://project-hobbit.eu/.

  3. 3.

    http://downloads.dbpedia.org/2016-10/core-i18n/.

  4. 4.

    https://github.com/AKSW/gerbil/wiki/Question-Answering.

  5. 5.

    http://gerbil-qa.aksw.org/gerbil/.

  6. 6.

    http://master.project-hobbit.eu/.

References

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  6. Usbeck, R., et al.: Benchmarking question answering systems. Semant. Web J. (2018)

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  7. Zimina, E., et al.: GQA: grammatical question answering for RDF data. In: Recupero, D.R., Buscaldi, D. (eds.), Semantic Web Challenges, Cham. Springer International Publishing (2018)

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Acknowledgements

This work was supported by the European Union’s H2020 research and innovation action HOBBIT under the Grant Agreement number 688227.

Author information

Authors and Affiliations

  1. Fraunhofer-Institute IAIS, Sankt Augustin, Germany

    Giulio Napolitano

  2. Data Science Group, University of Paderborn, Paderborn, Germany

    Ricardo Usbeck & Axel-Cyrille Ngonga Ngomo

Authors
  1. Giulio Napolitano
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  2. Ricardo Usbeck
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  3. Axel-Cyrille Ngonga Ngomo
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Corresponding author

Correspondence to Giulio Napolitano .

Editor information

Editors and Affiliations

  1. Laboratoire d'Informatique de Paris-Nord, Paris 13 University, Villetaneuse, France

    Davide Buscaldi

  2. University of Bologna, Bologna, Italy

    Aldo Gangemi

  3. Department of Mathematics and Computer Science, University of Cagliari, Cagliari, Italy

    Diego Reforgiato Recupero

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Napolitano, G., Usbeck, R., Ngomo, AC.N. (2018). The Scalable Question Answering Over Linked Data (SQA) Challenge 2018. In: Buscaldi, D., Gangemi, A., Reforgiato Recupero, D. (eds) Semantic Web Challenges. SemWebEval 2018. Communications in Computer and Information Science, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-00072-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-00072-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00071-4

  • Online ISBN: 978-3-030-00072-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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