Computation of semantic number from morphological information

Iris Berent, Steven Pinker, Joseph Tzelgov, Uri Bibi, Liat Goldfarb

Research output: Contribution to journalArticlepeer-review

Abstract

The distinction between singular and plural enters into linguistic phenomena such as morphology, lexical semantics, and agreement and also must interface with perceptual and conceptual systems that assess numerosity in the world. Three experiments examine the computation of semantic number for singulars and plurals from the morphological properties of visually presented words. In a Stroop-like task, Hebrew speakers were asked to determine the number of words presented on a computer screen (one or two) while ignoring their contents. People took longer to respond if the number of words was incongruent with their morphological number (e.g., they were slower to determine that one word was on the screen if it was plural, and in some conditions, that two words were on the screen if they were singular, compared to neutral letter strings), suggesting that the extraction of number from words is automatic and yields a representation comparable to the one computed by the perceptual system. In many conditions, the effect of number congruency occurred only with plural nouns, not singulars, consistent with the suggestion from linguistics that words lacking a plural affix are not actually singular in their semantics but unmarked for number.

Original languageEnglish
Pages (from-to)342-358
Number of pages17
JournalJournal of Memory and Language
Volume53
Issue number3
DOIs
StatePublished - Sep 2005
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by NIH Grants R29 DC03277 and HD 18381. We thank Grev Corbett for discussion of this project.

Keywords

  • Hebrew
  • Morphology
  • Numerosity
  • Semantics
  • Stroop

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Artificial Intelligence

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