Abstract

In the project we describe, we have taken a basic core of about 5000 synsets in WordNet that are the most frequently used, and we have categorized these into sixteen broad categories, including, for example, time, space, scalar notions, composite entities, and event structure. We have sketched out the structure of some of the underlying abstract core theories of commonsense knowledge, including those for the mentioned areas. These theories explicate the basic predicates in terms of which the most common word senses need to be defined or characterized. We are now encoding axioms that link the word senses to the core theories. This may be thought of as a kind of “advanced lexical decomposition”, where the “primitives” into which words are “decomposed” are elements in coherently worked-out theories. In this paper we focus on our work on the 450 of these synsets that are concerned with events and their structure.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baker, C., Fillmore, C., Cronin, B.: The Structure of the Framenet Database. International Journal of Lexicography 16(3), 281–296 (2003)CrossRefGoogle Scholar
  2. 2.
    Bock, C., Gruninger, M.: PSL: A Semantic Domain for Flow Models. Software and Systems Modeling Journal 4(2), 209–231 (2005)CrossRefGoogle Scholar
  3. 3.
    Boyd-Graber, J., Fellbaum, C., Osherson, D., Schapire, R.: Adding dense, weighted, connections to WordNet. In: Proceedings of the Third Global WordNet Meeting, Jeju Island, Korea (January 2006)Google Scholar
  4. 4.
    Guha, R., Lenat, D.: CYC: A Midterm Report. AI Magazine 11(3), 33–59 (1990)Google Scholar
  5. 5.
    Harabagiu, S., Moldovan, D.: Enriching the WordNet Taxonomy with Contextual Knowledge Acquired from Text. In: Shapiro, S., Iwanska, L. (eds.) Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language, pp. 301–334. AAAI/MIT Press, Cambridge (2000)Google Scholar
  6. 6.
    Miller, G.: WordNet: a lexical database for English. Communications of the ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  7. 7.
    Niles, I., Pease, A.: Toward a Standard Upper Ontology. In: Welty, C., Smith, B. (eds.) Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS 2001), Ogunquit, Maine (October 2001)Google Scholar
  8. 8.
    Pantel, P., Lin, D.: Discovering Word Senses from Text. In: Proceedings of ACM Conference on Knowledge Discovery and Data Mining (KDD 2002), Edmonton, Canada, pp. 613–619 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jerry R. Hobbs
    • 1
  1. 1.Information Sciences InstituteUniversity of Southern CaliforniaMarina del Rey 

Personalised recommendations