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The jobs puzzle: Taking on the challenge via controlled natural language processing

  • ROLF SCHWITTER (a1)

Abstract

In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle.

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Balduccini, M., Baral, C. and Lierler, Y. 2008. Knowledge representation and question answering. In Handbook of Knowledge Representation, van Harmelen, F., Lifschitz, V. and Porter, B., Eds. Elsevier B. V., 779819.
Baral, C. and Dzifcak, J. 2012. Solving puzzles described in english by automated translation to answer set programming and learning how to do that translation. In Proceedings of KR 2012, 573–577.
Brewka, G., Eiter, T. and Truszczyński, M. December, 2011. Answer set programming at a glance. Communications of the ACM 54, 12.
Finkel, R., Marek, V. W. and Truszczyński, M. 2004. Constraint Lingo: Towards high-level constraint programming. Software: Practice and Experience 34, 15, 14811504.
Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T. and Schneider, M. 2011. Potassco: The potsdam answer set solving collection. AI Communications 24, 2, 105124.
Gelfond, M. and Lifschitz, V. 1988. The stable model semantics for logic programming. In Proceedings of International Logic Programming Conference and Symposium, Kowalski, R. and Bowen, K., Eds. 10701080.
Kamp, H. and Reyle, U. 1993. From Discourse to Logic: Introduction to Modeltheoretic Semantics of Natural Language, Formal Logic and Discourse Representation Theory. Kluwer, Dordrecht.
Lierler, Y. and Görz, G. 2006. Model generation for generalized quantifiers via answer set programming. In Proceedings of 8th Conference on Natural Language Processing (KONVENS), 101–106.
Lifschitz, V. 2008. What is answer set programming? In Proceedings of AAAI'08, vol. 3, 15941597.
Niemelä, I., Simons, P. and Syrjänen, T. 2000. Smodels: A system for answer set programming. In CoRR, Vol. cs.AI/0003033.
Schwitter, R. 2010. Controlled natural language for knowledge representation. In Proceedings of COLING 2010, 1113–1121.
Schwitter, R. 2012. Answer set programming via controlled natural language processing. In CNL 2012, Kuhn, T. and Fuchs, N. E., Eds., LNCS 7427, Springer, 2643.
Schwitter, R., Ljungberg, A. and Hood, D. 2003. ECOLE - A look-ahead editor for a controlled language. In Proceedings of EAMT-CLAW03, May 15–17, Dublin City University, Ireland, 141150.
Shapiro, S. C. 2011. The jobs puzzle: A challenge for logical expressibility and automated reasoning. In Logical Formalizations of Commonsense Reasoning, Davis, E., Doherty, P. and Erdem, E., Eds., AAAI Press, Menlo Park, CA, 96102.
Shapiro, S. C. and the SNePS Implementation Group. December 8, 2010. SNePS 2.7.1 User's Manual. Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY.
Sutcliffe, G. 2009. The TPTP problem library and associated infrastructure: The FOF and CNF parts, v3.5.0. Journal of Automated Reasoning, 43, 4, 337362.
Syrjänen, T. 2000. Lparse 1.0, User's Manual. Laboratory for Theoretical Computer Science, Helsinki University of Technology.
Todorova, Y. 2011. Answering questions about dynamic domains from natural language using ASP. Dissertation, Texas Tech University.
van Eijck, J. and Kamp, H. 2011. Discourse representation in context. In Handbook of Logic and Language, 2nd ed., van Benthem, J. and ter Meulen, A., Eds. Elsevier, 181252.
White, C. and Schwitter, R. 2009. An update on PENG light. In Proceedings of ALTA 2009, 80–88.
Wos, L., Overbeek, R., Lusk, E. and Boyle, J. 1984. Automated Reasoning: Introduction and Applications. Prentice-Hall, New Jersey.

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The jobs puzzle: Taking on the challenge via controlled natural language processing

  • ROLF SCHWITTER (a1)

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