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QaldGen: Towards Microbenchmarking of Question Answering Systems over Knowledge Graphs

  • Kuldeep SinghEmail author
  • Muhammad Saleem
  • Abhishek Nadgeri
  • Felix Conrads
  • Jeff Z. Pan
  • Axel-Cyrille Ngonga Ngomo
  • Jens Lehmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11779)

Abstract

Over the last years, a number of Knowledge Graph (KG) based Question Answering (QA) systems have been developed. Consequently, the series of Question Answering Over Linked Data (QALD1–QALD9) challenges and other datasets have been proposed to evaluate these systems. However, the QA datasets contain a fixed number of natural language questions and do not allow users to select micro benchmarking samples of the questions tailored towards specific use-cases. We propose QaldGen, a framework for microbenchmarking of QA systems over KGs which is able to select customised question samples from existing QA datasets. The framework is flexible enough to select question samples of varying sizes and according to the user-defined criteria on the most important features to be considered for QA benchmarking. This is achieved using different clustering algorithms. We compare state-of-the-art QA systems over knowledge graphs by using different QA benchmarking samples. The observed results show that specialised micro-benchmarking is important to pinpoint the limitations of the various QA systems and its components.

Resource Type: Evaluation benchmarks or Methods

Repository: https://github.com/dice-group/qald-generator

License: GNU General Public License v3.0

Notes

Acknowledgments

This work has been supported by the project LIMBO (Grant no. 19F2029I), OPAL (no. 19F2028A), KnowGraphs (no. 860801), and SOLIDE (no. 13N14456)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kuldeep Singh
    • 1
    Email author
  • Muhammad Saleem
    • 2
  • Abhishek Nadgeri
    • 3
  • Felix Conrads
    • 2
  • Jeff Z. Pan
    • 5
    • 6
  • Axel-Cyrille Ngonga Ngomo
    • 4
  • Jens Lehmann
    • 7
  1. 1.Nuance Communications Deutschland GmbHAachenGermany
  2. 2.University of LeipzigLeipzigGermany
  3. 3.Service Lee TechnologiesMumbaiIndia
  4. 4.University of PaderbornPaderbornGermany
  5. 5.Edinburgh Research Centre, HuaweiEdinburghUK
  6. 6.University of AberdeenAberdeenUK
  7. 7.Fraunhofer IAISSankt AugustinGermany

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