Taking SPARQL 1.1 Extensions into Account in the SWIP System

  • Fabien Amarger
  • Ollivier Haemmerlé
  • Nathalie Hernandez
  • Camille Pradel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7735)


The SWIP system aims at hiding the complexity of expressing a query in a graph query language such as SPARQL. We propose a mechanism by which a query expressed in natural language is translated into a SPARQL query. Our system analyses the sentence in order to exhibit concepts, instances and relations. Then it generates a query in an internal format called the pivot language. Finally, it selects pre-written query patterns and instantiates them with regard to the keywords of the initial query. These queries are presented by means of explicative natural language sentences among which the user can select the query he/she is actually interested in. We are currently focusing on new kinds of queries which are handled by the new version of our system, which is now based on the 1.1 version of SPARQL.


Natural Language Language Query Projection Attribute User Query SPARQL Query 
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.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semantic Web Inf. Syst. 5(3), 1–22 (2009)CrossRefGoogle Scholar
  2. 2.
    Athanasis, N., Christophides, V., Kotzinos, D.: Generating On the Fly Queries for the Semantic Web: The ICS-FORTH Graphical RQL Interface (GRQL). In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 486–501. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Russell, A., Smart, P.R.: Nitelight: A graphical editor for sparql queries. In: Bizer, C., Joshi, A. (eds.) International Semantic Web Conference (Posters & Demos). CEUR Workshop Proceedings, vol. 401. (2008)Google Scholar
  4. 4.
    Ferré, S., Hermann, A.: Semantic Search: Reconciling Expressive Querying and Exploratory Search. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 177–192. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    CoGui. A conceptual graph editor. Web site (2009),
  6. 6.
    Elbassuoni, S., Ramanath, M., Schenkel, R., Weikum, G.: Searching rdf graphs with sparql and keywords. IEEE Data Eng. Bull. 33(1), 16–24 (2010)Google Scholar
  7. 7.
    Lei, Y., Uren, V.S., Motta, E.: SemSearch: A Search Engine for the Semantic Web. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 238–245. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Zhou, Q., Wang, C., Xiong, M., Wang, H., Yu, Y.: SPARK: Adapting Keyword Query to Semantic Search. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 694–707. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Tran, T., Wang, H., Rudolph, S., Cimiano, P.: Top-k exploration of query candidates for efficient keyword search on graph-shaped (rdf) data. In: ICDE, pp. 405–416. IEEE (2009)Google Scholar
  10. 10.
    Comparot, C., Haemmerlé, O., Hernandez, N.: An Easy Way of Expressing Conceptual Graph Queries from Keywords and Query Patterns. In: Croitoru, M., Ferré, S., Lukose, D. (eds.) ICCS 2010. LNCS, vol. 6208, pp. 84–96. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Pradel, C., Haemmerlé, O., Hernandez, N.: Expressing Conceptual Graph Queries from Patterns: How to Take into Account the Relations. In: Andrews, S., Polovina, S., Hill, R., Akhgar, B. (eds.) ICCS 2011. LNCS (LNAI), vol. 6828, pp. 229–242. Springer, Heidelberg (2011)Google Scholar
  12. 12.
    Pradel, C., Haemmerlé, O., Hernandez, N.: A Semantic Web Interface Using Patterns: The SWIP System. In: Croitoru, M., Rudolph, S., Wilson, N., Howse, J., Corby, O. (eds.) GKR 2011. LNCS, vol. 7205, pp. 172–187. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Harris, S., Seaborne, A.: Sparql 1.1 query language. w3c working draft (July 24, 2012), World Wide Web Consortium,
  14. 14.
    Nivre, J., Hall, J., Nilsson, J., Chanev, A., Eryigit, G., Kübler, S., Marinov, S., Marsi, E.: Maltparser: A language-independent system for data-driven dependency parsing. Natural Language Engineering 13(02), 95–135 (2007)Google Scholar
  15. 15.
    Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 10, 707–710 (1966)MathSciNetGoogle Scholar
  16. 16.
    Alkhateeb, F., Baget, J.-F., Euzenat, J.: Extending sparql with regular expression patterns (for querying rdf). J. Web Sem. 7(2), 57–73 (2009)CrossRefGoogle Scholar
  17. 17.
    Kjernsmo, K., Passant, A.: Sparql new features and rationale. World Wide Web Consortium, Working Draft WD-sparql-features-20090702 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fabien Amarger
    • 1
  • Ollivier Haemmerlé
    • 1
  • Nathalie Hernandez
    • 1
  • Camille Pradel
    • 1
  1. 1.Département de Mathématiques-InformatiqueIRIT, Université de Toulouse le MirailToulouse CedexFrance

Personalised recommendations