Analogical Generalization and Retrieval for Denominal Verb Interpretation

Clifton J. McFate, Kenneth D. Forbus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The creativity of natural language poses a significant theoretical problem. One example of this is denominal verbs (those derived from nouns) such as spoon in “She spooned me some sugar”. Traditional generative approaches typically posit a unique entry in the lexicon for this usage, though this approach has difficulty scaling. Construction Grammar has evolved as a competing theory which instead allows the syntactic form of the sentence itself to contribute semantic meaning. However, how people learn syntactic constructions remains an open question. One suggestion has been that they are learned through analogical generalization. We evaluate this hypothesis using a computational model of analogical generalization to simulate Kaschak and Glenberg's (2000) study regarding interpretation of denominal verbs.

Original languageEnglish (US)
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages1277-1282
Number of pages6
ISBN (Electronic)9780991196739
StatePublished - 2016
Externally publishedYes
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: Aug 10 2016Aug 13 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period8/10/168/13/16

Keywords

  • Analogical Generalization
  • Analogy
  • Construction Grammar
  • Linguistics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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