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Towards Multilingual Neural Question Answering

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 909))

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Abstract

Cross-lingual and multilingual question answering is a critical part of a successful and accessible natural language interface. However, many current solutions are unsatisfactory. We believe that recent developments in deep learning approaches are likely to be efficient for question answering tasks spanning several languages. This work aims to discuss current achievements and remaining challenges. We outline requirements and suggestions for practical parallel data collection and describe existing methods and datasets. We also demonstrate that a simple translation of texts can be inadequate in case of Arabic, English and German languages (on InsuranceQA and SemEval datasets), and thus more sophisticated models are required. We hope that our findings will ignite interest in neural approaches to multilingual question answering.

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Notes

  1. 1.

    The parameters are as follows: skip-gram, window 5, negative-sampling rate −1/1000.

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Acknowledgements

This work was partially supported by the German Federal Ministry of Education and Research (BMBF) through the project DEEPLEE (01IW17001).

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Authors and Affiliations

  1. DFKI, Saarbrücken, Germany

    Ekaterina Loginova, Stalin Varanasi & Günter Neumann

Authors
  1. Ekaterina Loginova
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  2. Stalin Varanasi
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  3. Günter Neumann
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Corresponding author

Correspondence to Ekaterina Loginova .

Editor information

Editors and Affiliations

  1. Eötvös Loránd University, Budapest, Hungary

    András Benczúr

  2. Abt. Informatik, Universität Kiel, Kiel, Germany

    Bernhard Thalheim

  3. Eötvös Loránd University, Budapest, Hungary

    Tomáš Horváth

  4. Politecnico di Torino, Turin, Italy

    Silvia Chiusano

  5. Polytechnic University of Turin, Turin, Italy

    Tania Cerquitelli

  6. Hungarian Academy of Sciences, Budapest, Hungary

    Csaba Sidló

  7. University of Nebraska–Lincoln, Lincoln, NE, USA

    Peter Z. Revesz

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Loginova, E., Varanasi, S., Neumann, G. (2018). Towards Multilingual Neural Question Answering. In: Benczúr, A., et al. New Trends in Databases and Information Systems. ADBIS 2018. Communications in Computer and Information Science, vol 909. Springer, Cham. https://doi.org/10.1007/978-3-030-00063-9_26

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  • DOI: https://doi.org/10.1007/978-3-030-00063-9_26

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