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GKC: A Reasoning System for Large Knowledge Bases

  • Tanel TammetEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11716)

Abstract

This paper introduces GKC, a resolution prover optimized for search in large knowledge bases. The system is built upon a shared memory graph database Whitedb, enabling it to solve multiple different queries without a need to repeatedly parse or load the large parsed knowledge base from the disk. Due to the relatively shallow and simple structure of most of the literals in the knowledge base, the indexing methods used are mostly hash-based. While GKC performs well on large problems from the TPTP set, the system is built for use as a core system for developing a toolset of commonsense reasoning functionalities.

Keywords

Automated reasoning Knowledge base 

References

  1. 1.
  2. 2.
    Tammet, T.: Gandalf. J. Autom. Reason. 18(2), 199–204 (1997)CrossRefGoogle Scholar
  3. 3.
    Tammet, T.: Towards efficient subsumption. In: Kirchner, C., Kirchner, H. (eds.) CADE 1998. LNCS, vol. 1421, pp. 427–441. Springer, Heidelberg (1998).  https://doi.org/10.1007/BFb0054276 CrossRefGoogle Scholar
  4. 4.
    Pease, A., Sutcliffe, G.: First order reasoning on a large ontology. In: Proceedings of the CADE-21 Workshop on Empirically Successful Automated Reasoning in Large Theories, vol. 257, pp. 61–70. CEUR Workshop Proceedings (2007)Google Scholar
  5. 5.
    Reagan, S.P., Sutcliffe, G., Goolsbey, K., Kahlert, R.C.: The Cyc TPTP Challenge Problem Set. Unpublished manuscript. http://www.opencyc.org/doc/tptp_challenge_problem_set
  6. 6.
    Suchanek, F., Kasneci, G.m Weikum, G.: YAGO: a core of semantic knowledge. In: Proceedings of the 16th International World Wide Web Conference, Banff, Canada, pp. 697–706Google Scholar
  7. 7.
    Sutcliffe, G.: The TPTP world – infrastructure for automated reasoning. In: Clarke, E.M., Voronkov, A. (eds.) LPAR 2010. LNCS (LNAI), vol. 6355, pp. 1–12. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-17511-4_1 CrossRefGoogle Scholar
  8. 8.
    Suda, M., Weidenbach, C., Wischnewski, P.: On the saturation of YAGO. In: Giesl, J., Hähnle, R. (eds.) IJCAR 2010. LNCS (LNAI), vol. 6173, pp. 441–456. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-14203-1_38CrossRefGoogle Scholar
  9. 9.
    Bachmair, L., Ganzinger, H.: Resolution theorem proving. In: Handbook of Automated Reasoning, pp. 19–99. Elsevier (2001)Google Scholar
  10. 10.
    Kovács, L., Voronkov, A.: First-order theorem proving and Vampire. In: Sharygina, N., Veith, H. (eds.) CAV 2013. LNCS, vol. 8044, pp. 1–35. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-39799-8_1CrossRefGoogle Scholar
  11. 11.
    Schulz, S., Möhrmann, M.: Performance of clause selection heuristics for saturation-based theorem proving. In: Olivetti, N., Tiwari, A. (eds.) IJCAR 2016. LNCS (LNAI), vol. 9706, pp. 330–345. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-40229-1_23 CrossRefGoogle Scholar
  12. 12.
    Sekar, R., Ramakrishnan, I., Voronkov, A.: Term indexing. In: Handbook of Automated Reasoning, vol. II, chap. 26, pp. 1853–1964. Elsevier Science (2001)Google Scholar
  13. 13.
    Schulz, S.: Simple and efficient clause subsumption with feature vector indexing. In: Bonacina, M.P., Stickel, M.E. (eds.) Automated Reasoning and Mathematics. LNCS (LNAI), vol. 7788, pp. 45–67. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-36675-8_3CrossRefGoogle Scholar
  14. 14.
    Tammet, T., Järv, P.: WhiteDB homepage. https://whitedb.org
  15. 15.
    Furbach, U., Schon, C.: Commonsense reasoning meets theorem proving. In: Proceedings of the Workshop on Bridging the Gap between Human and Automated Reasoning co-located with 25th International Joint Conference on Artificial Intelligence IJCAI 2016, pp. 74–85. CEUR (2016)CrossRefGoogle Scholar
  16. 16.
    Sutcliffe, G.: The 9th IJCAR automated theorem proving system competition - CASC-J9. AI Commun. 31(1), 1–13 (2018)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Lopez Hernandez, J.C., Korovin, K.: An abstraction-refinement framework for reasoning with large theories. In: Galmiche, D., Schulz, S., Sebastiani, R. (eds.) IJCAR 2018. LNCS (LNAI), vol. 10900, pp. 663–679. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-94205-6_43CrossRefzbMATHGoogle Scholar
  18. 18.
    Tammet, T.: Repository of the GKC system and experiment logs (2019). https://github.com/tammet/gkc

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Tallinn University of TechnologyTallinnEstonia

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