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Logic Programming Infrastructure for Inferences on FrameNet

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3229))

Abstract

The growing size of electronically available text corpora like companies’ intranets or the WWW has made information access a hot topic within Computational Linguistics. Despite the success of statistical or keyword based methods, deeper Knowledge Representation (KR) techniques along with “inference” are often mentioned as mandatory, e.g. within the Semantic Web context, to enable e.g. better query answering based on “semantical” information. In this paper we try to contribute to the open question how to operationalize semantic information on a larger scale. As a basis we take the frame structures of the Berkeley FrameNet II project, which is a structured dictionary to explain the meaning of words from a lexicographic perspective. Our main contribution is a transformation of the FrameNet II frames into the answer set programming paradigm of logic programming.

Because a number of different reasoning tasks are subsumed under “inference” in the context of natural language processing, we emphasize the flexibility of our transformation. Together with methods for automatic annotation of text documents with frame semantics which are currently developed at various sites, we arrive at an infrastructure that supports experimentation with semantic information access as is currently demanded for.

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References

  1. Baral, C.: Knowledge representation, reasoning and declarative problem solving. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

  2. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F.: Description Logic Handbook. Cambridge University Press, Cambridge (2002)

    Google Scholar 

  3. Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet project. In: Proc. of COLING-ACL 1998, Montreal, Canada (1998)

    Google Scholar 

  4. Baumgartner, P., Kühn, M.: Abducing Coreference by Model Construction. Journal of Language and Computation 1(2), 175–190 (2000)

    Google Scholar 

  5. Bos, J.: Computational semantics in discourse: Underspecification, resolution, and inference. Journal of Logic, Language and Information 13(2), 139–157 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  6. de Nivelle, H., Blackburn, P., Bos, J., Kohlhase, M.: Inference and computational semantics. Studies in Linguistics and Philosophy, Computing Meaning 77(2), 11–28 (2001)

    Google Scholar 

  7. Eiter, T., Faber, W., Leone, N., Pfeifer, G.: Declarative problem-solving using the DLV system. In: Logic-based artificial intelligence, pp. 79–103. Kluwer, Dordrecht (2000)

    Google Scholar 

  8. Erk, K., Kowalski, A., Pado, S., Pinkal, M.: Towards a resource for lexical semantics:A large German corpus with extensive semantic annotation. In: Proc. of ACL 2003, Sapporo, Japan (2003)

    Google Scholar 

  9. Fellbaum, C. (ed.): WordNet. An electronic lexical database. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  10. Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Kowalski, R., Bowen, K. (eds.) Proc. of 5th ICLP (1988)

    Google Scholar 

  11. Hobbs, J.R., Stickel, M.E., Appelt, D.E., Martin, P.: Interpretation as abduction. Artificial Intelligence 63(1-2), 69–142 (1993)

    Article  Google Scholar 

  12. Kohlhase, M., Koller, A.: Resource-adaptive model generation as a performance model. Logic Journal of the IGPL 11(4), 435–456 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  13. Narayanan, S., Fillmore, C.J., Baker, C.F., Petruck, M.R.L.: FrameNet Meets the Semantic Web:A DAML+OIL Frame Representation. In: Proc. of AAAI (2002)

    Google Scholar 

  14. Niemelä, I., Simons, P.: Efficient implementation of the well-founded and stable model semantics. In: Proc. of JICSLP, Bonn, Germany, The MIT Press, Cambridge (1996)

    Google Scholar 

  15. Wernhard, C.: System Description: KRHyper. Fachberichte Informatik 14–2003, Universität Koblenz-Landau (2003)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Baumgartner, P., Burchardt, A. (2004). Logic Programming Infrastructure for Inferences on FrameNet. In: Alferes, J.J., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2004. Lecture Notes in Computer Science(), vol 3229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30227-8_49

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  • DOI: https://doi.org/10.1007/978-3-540-30227-8_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23242-1

  • Online ISBN: 978-3-540-30227-8

  • eBook Packages: Springer Book Archive

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