Introducing Feedback in Qanary: How Users Can Interact with QA Systems

  • Dennis Diefenbach
  • Niousha Hormozi
  • Shanzay Amjad
  • Andreas Both
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10577)


Providing a general and efficient Question Answering system over Knowledge Bases (KB) has been studied for years. Most of the works concentrated on the automatic translation of a natural language question into a formal query. However, few works address the problem on how users can interact with Question Answering systems during this translation process. We present a general mechanism that allows users to interact with Question Answering systems. It is built on top of Qanary, a framework for integrating Question Answering components. We show how the mechanism can be applied in a generalized way. In particular, we show how it can be used when the user asks ambiguous questions.


User interaction Question answering systems User interface 



This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 642795.


  1. 1.
    Both, A., Diefenbach, D., Singh, K., Shekarpour, S., Cherix, D., Lange, C.: Qanary – a methodology for vocabulary-driven open question answering systems. In: Sack, H., Blomqvist, E., dAquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 625–641. Springer, Cham (2016). Scholar
  2. 2.
    Damljanovic, D., Agatonovic, M., Cunningham, H.: Freya: an interactive way of querying linked data using natural language. In: García-Castro, R., Fensel, D., Antoniou, G. (eds.) ESWC 2011. LNCS, vol. 7117, pp. 125–138. Springer, Heidelberg (2012). Scholar
  3. 3.
    Diefenbach, D., Amjad, S., Both, A., Singh, K., Maret, P.: Trill: a reusable Front-End for QA systems. In: ESWC P&D (2017)Google Scholar
  4. 4.
    Diefenbach, D., Singh, K., Both, A., Cherix, D., Lange, C., Auer, S.: The qanary ecosystem: getting new insights by composing question answering pipelines. In: ICWE (2017)Google Scholar
  5. 5.
    Diefenbach, D., Singh, K., Maret, P.: WDAqua-core0: a question answering component for the research community. In: ESWC, 7th Open Challenge on Question Answering over Linked Data (QALD-7) (2017)CrossRefGoogle Scholar
  6. 6.
    Ferrández, Ó., Spurk, C.H., Kouylekov, M., Dornescu, I., Ferrández, S., Negri, M., Izquierdo, R., Tomás, T., Orasan, C., Neumann, G., Magnini, B., González, J.L.V.: The QALL-ME framework: a specifiable-domain multilingual question answering architectureGoogle Scholar
  7. 7.
    Kaufmann, E., Bernstein, A., Zumstein, R.: Querix: a natural language interface to query ontologies based on clarification dialogs. In: ISWC (2006)Google Scholar
  8. 8.
    Lopez, V., Unger, C., Cimiano, P., Motta, E.: Evaluating question answering over linked data. Web Semant. Sci. Serv. Agents World Wide Web (2013)CrossRefGoogle Scholar
  9. 9.
    Marx, E., Usbeck, R., Ngonga Ngomo, A., Höffner, K., Lehmann, J., Auer, S.: Towards an open question answering architecture. In: SEMANTICS (2014)Google Scholar
  10. 10.
    Mazzeo, G.M., Zaniolo, C.: Question answering on RDF KBs using controlled natural language and semantic auto completion. Semant. Web J. (2016)Google Scholar
  11. 11.
    Singh, K., Both, A., Diefenbach, D., Shekarpour, S.: Towards a message-driven vocabulary for promoting the interoperability of question answering systems. In: ICSC (2016)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Dennis Diefenbach
    • 1
  • Niousha Hormozi
    • 2
  • Shanzay Amjad
    • 3
  • Andreas Both
    • 4
  1. 1.Lab. Hubert CurienSaint EtienneFrance
  2. 2.University of AthensAthensGreece
  3. 3.University of OttawaOttawaCanada
  4. 4.DATEV eGNurembergGermany

Personalised recommendations