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The Deep Lexical Semantics of Event Words

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Frames and Concept Types

Part of the book series: Studies in Linguistics and Philosophy ((SLAP,volume 94))

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Abstract

We have selected a basic core of about 5,000 synsets in WordNet that are the most frequently used, and we categorized these into 16 broad categories, including, for example, time, space, scalar notions, composite entities, and event structure. We 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 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.

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Notes

  1. 1.

    In this paper we use a subset of Common Logic (http://common-logic.org/) for the syntax of our notation.

  2. 2.

    CoreWordNet is downloadable from http://wordnet.cs.princeton.edu/downloads.html.

  3. 3.

    http://www.rutumulkar.com/download/NL-Pipeline/NL-Pipeline.php.

  4. 4.

    http://rutumulkar.com/download/TACITUS/tacitus.php.

  5. 5.

    Descriptions of all the core theories, with axioms, can be found at http://www.isi.edu/~hobbs/csk.html.

References

  • Baker, Collin F., Charles J. Fillmore, and Beau Cronin. 2003. The structure of the FrameNet database. International Journal of Lexicography 16(3): 281–296.

    Article  Google Scholar 

  • Bock, C., and M. Gruninger. 2005. A semantic domain for flow models. Software and Systems Modeling Journal 4(2): 209–231.

    Article  Google Scholar 

  • Boyd-Graber, J., C. Fellbaum, D. Osherson, and R. Schapire. 2006. Adding dense, weighted, connections to wordnet. In Proceedings of the third global WordNet meeting, Jeju Island.

    Google Scholar 

  • Gruber, Jeffrey C. 1965. Studies in lexical relations. Ph.D. dissertation, Massachusetts Institute of Technology.

    Google Scholar 

  • Gruninger, Michael, and Christopher Menzel. 2010. The process specification language (PSL): Theory and applications. AI Magazine 24(3).

    Google Scholar 

  • Guha, R.V., and D.B. Lenat. 1990. CYC: A midterm report. AI Magazine 11(3): 33–59.

    Google Scholar 

  • Harabagiu, Sanda, and Dan Moldovan. 2000. Enriching the WordNet taxonomy with contextual knowledge acquired from text. In Natural language processing and knowledge representation: Language for knowledge and knowledge for language, ed. S. Shapiro and L. Iwanska, 301–334. Menlo Park: AAAI.

    Google Scholar 

  • Hobbs, Jerry R. 1985. Ontological promiscuity. In Proceedings of the 23rd annual meeting of the association for computational linguistics, Chicago, 61–69.

    Google Scholar 

  • Hobbs, Jerry R. 2008. Deep lexical semantics. In Proceedings of the 9th international conference on intelligent text processing and computational linguistics (CICLing-2008), Haifa.

    Google Scholar 

  • Hobbs, Jerry R., Mark Stickel, Douglas Appelt, and Paul Martin. 1993. Interpretation as abduction. Artificial Intelligence 63(1–2): 69–142.

    Article  Google Scholar 

  • Jackendoff, Ray. 1972. Semantic interpretation in generative grammar. Cambridge: MIT.

    Google Scholar 

  • Kipper, Karin, Anna Korhonen, Neville Ryant, and Martha Palmer. 2006. A large-scale extension of VerbNet with novel verb classes. In Proceedings of the 12th euralex international congress (euralex 2006), Turin.

    Google Scholar 

  • Lakoff, George. 1987. Women, fire, and dangerous things: What categories reveal about the mind. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • McCarthy, John. 1980. Circumscription: A form of nonmonotonic reasoning. Artificial Intelligence 13: 27–39.

    Article  Google Scholar 

  • Miller, George A. 1995. WordNet: A lexical database for English. Communications of the ACM 38(11): 39–41.

    Article  Google Scholar 

  • Mueller, Erik T. 1988. Commonsense reasoning. San Mateo: Morgan Kaufmann.

    Google Scholar 

  • Mulkar, Rutu, Jerry Hobbs, and Eduard Hovy. 2011. Learning from reading syntactically complex biology texts. In Proceedings of the AAAI spring symposium commonsense’07, Stanford.

    Google Scholar 

  • Niles, Ian, and Adam Pease. 2001. Towards a standard upper ontology. In Proceedings of the 2nd international conference on formal ontology in information systems (FOIS-2001), Ogunquit, ed. Chris Welty and Barry Smith.

    Google Scholar 

  • Ovchinnikova, Ekaterina, N. Montazeri, Theodore Alexandrov, Jerry Hobbs, M. McCord, and Rutu Mulkar-Mehtag. 2011. Abductive reasoning with a large knowledge base for discourse processing. In Proceedings of the 9th international workshop on computational semantics, Oxford.

    Google Scholar 

  • Pantel, Patrick, and Dekang Lin. 2002. Discovering word senses from text. In Proceedings of ACM conference on knowledge discovery and data mining (KDD-02), Edmonton, 613–619.

    Google Scholar 

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Acknowledgements

We have profited from discussions with Peter Clark, Christiane Fellbaum, Rutu Mulkar-Mehta, and Katya Ovchinnikova. This research was supported in part by the Defense Advanced Research Projects Agency (DARPA) Machine Reading Program under Air Force Research Laboratory (AFRL) prime contract no. FA8750-09-C-0172, in part by the Office of Naval Research under contract no. N00014-09-1-1029, and in part by the IARPA (DTO) AQUAINT program, contract N61339-06-C-0160. Any opinions, findings, and conclusion or recommendations expressed in this material are those of the authors and do not necessarily reflect the view of the DARPA, AFRL, ONR, IARPA, or the US government.

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Correspondence to Jerry R. Hobbs .

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Hobbs, J.R., Montazeri, N. (2014). The Deep Lexical Semantics of Event Words. In: Gamerschlag, T., Gerland, D., Osswald, R., Petersen, W. (eds) Frames and Concept Types. Studies in Linguistics and Philosophy, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-01541-5_7

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