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An Effective Corpus-Based Question Answering Pipeline for Italian

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Intelligent Interactive Multimedia Systems and Services 2017 (KES-IIMSS-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 76))

Abstract

Question Answering is a longevous field in computer science, aimed at realizing systems able to answer questions expressed in natural language. However, building Question Answering systems for Italian and able to extract answers from a corpus pertaining a closed domain is still an open research problem. Indeed, extracting clues from a question to generate a query for the information retrieval engine as well as determining the likelihood that a candidate answer is correct are two very thorny tasks. To face these issues, the paper presents a Question Answering pipeline for Italian and based on a corpus of documents pertaining a closed domain. In particular, this pipeline exhibits functionalities for: (i) analyzing natural language questions in Italian by using lexical features; (ii) handling both factoid and description answer types and, depending on them, filtering contextual stop words from questions; (iii) scoring and selecting candidate answers with respect to their type in order to determine the best one. The proposed solution has been subject to an evaluation of its performance using standard metrics, showing promising results.

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Notes

  1. 1.

    https://uima.apache.org/.

  2. 2.

    http://wiki.dbpedia.org/.

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Authors and Affiliations

  1. National Research Council of Italy, Institute for High Performance Computing and Networking - ICAR, Via Pietro Castellino 111, 80131, Naples, Italy

    Emanuele Damiano, Raffaele Spinelli, Massimo Esposito & Giuseppe De Pietro

Authors
  1. Emanuele Damiano
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  2. Raffaele Spinelli
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  3. Massimo Esposito
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  4. Giuseppe De Pietro
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Corresponding author

Correspondence to Emanuele Damiano .

Editor information

Editors and Affiliations

  1. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Giuseppe De Pietro

  2. National Research Council of Italy (CNR-ICAR), Institute for High-Performance Computing and Networking, Naples, Italy

    Luigi Gallo

  3. Fern Barrow, Bournemouth University, Poole, Dorset, United Kingdom

    Robert J. Howlett

  4. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Damiano, E., Spinelli, R., Esposito, M., De Pietro, G. (2018). An Effective Corpus-Based Question Answering Pipeline for Italian. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-59480-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59479-8

  • Online ISBN: 978-3-319-59480-4

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