Question Answering with Imperfect Temporal Information

  • Steven Schockaert
  • David Ahn
  • Martine De Cock
  • Etienne E. Kerre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4027)


A temporal question answering system must be able to deduce which qualitative temporal relation holds between two events, a reasoning task that is complicated by the fact that historical events tend to have a gradual beginning and ending. In this paper, we introduce an algebra of temporal relations that is well–suited to represent the qualitative temporal information we have at our disposal. We provide a practical algorithm for deducing new temporal knowledge, and show how this can be used to answer questions that require several pieces of qualitative and quantitative temporal information to be combined. Finally, we propose a heuristic technique to cope with inconsistencies that may arise when integrating qualitative and quantitative information.


Temporal Information Temporal Relation Fuzzy Relation Question Answering Fuzzy Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ahn, D., Schockaert, S., De Cock, M., Kerre, E.E.: Supporting Temporal Question Answering: Strategies for Offline Data Collection. In: International workshop on Inference in Computational Semantics (to appear)Google Scholar
  2. 2.
    Allen, J.F.: Maintaining Knowledge about Temporal Intervals. Communications of the ACM 26, 832–843 (1983)MATHCrossRefGoogle Scholar
  3. 3.
    Badaloni, S., Giacomin, M.: A Fuzzy Extension of Allen#146s Interval Algebra. In: Lamma, E., Mello, P. (eds.) AI*IA 1999. LNCS, vol. 1792, pp. 155–165. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  4. 4.
    Dubois, D., HadjAli, A., Prade, H.: Fuzziness and Uncertainty in Temporal Reasoning. Journal of Universal Computer Science 9, 1168–1194 (2003)MathSciNetGoogle Scholar
  5. 5.
    Harabagiu, S., Bejan, C.A.: Question Answering based on Temporal Inference. In: AAAI 2005 Workshop on Inference for Textual Question Answering (2005)Google Scholar
  6. 6.
    Jijkoun, V., Tjong Kim Sang, E., Ahn, D., Müller, K., de Rijke, M.: The University of Amsterdam at QA@CLEF 2005. Working Notes for the CLEF 2005 Workshop (2005)Google Scholar
  7. 7.
    Renz, J., Ligozat, G.: Weak composition for qualitative spatial and temporal reasoning. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 534–548. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Saquete, E., Martínez–Barco, P., Muñozn, R., Vicedo, J.: Splitting Complex Temporal Questions for Question Answering Systems. In: ACL 2004, pp. 566–573 (2004)Google Scholar
  9. 9.
    Schockaert, S., De Cock, M., Kerre, E.E.: Imprecise Temporal Interval Relations. In: Bloch, I., Petrosino, A., Tettamanzi, A.G.B. (eds.) WILF 2005. LNCS, vol. 3849, pp. 108–113. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Schockaert, S., De Cock, M., Kerre, E.E.: Fuzzifying Allen’s Temporal Interval Relations (submitted)Google Scholar
  11. 11.
    Schockaert, S.: Construction of Membership Functions for Fuzzy Time Periods. In: Proceedings of the ESSLLI 2005 Student Session, pp. 297–305 (2005)Google Scholar
  12. 12.
    Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Steven Schockaert
    • 1
  • David Ahn
    • 2
  • Martine De Cock
    • 1
  • Etienne E. Kerre
    • 1
  1. 1.Department of Applied Mathematics and Computer ScienceGhent UniversityGentBelgium
  2. 2.ISLAUniversity of AmsterdamAmsterdam SJThe Netherlands

Personalised recommendations