<OT> New Posting: ROA-672

[roa at ruccs.rutgers.edu]

ROA 672-0804

Extraction, Gradedness, and Optimality

Frank Keller <keller at inf.ed.ac.uk>

Direct link: http://roa.rutgers.edu/view.php3?roa=672


Abstract:
Recently, a number of researcher have proposed the use of
experimental methods to elicit acceptability judgments,
thus addressing the shortcomings of the conventional intuitive
way of gathering linguistic data (cf. Bard et al. 1996,
Cowart 1997, Schütze 1996). The use of experimental methods
allows to handle inter- and intraspeaker variation and to
control for known biases on judgment behavior (cf. Schütze
1996). An experimental approach seems particularly important
for the study of linguistic phenomena involving degrees
of grammaticality, and recently, several experimental investigati
on of gradedness have become available (cf. Cowart 1994,
Keller 1996a,b, Neville 1991). So far, however, no theoretical
framework exists that offers a systematic way of dealing
with graded data.

This paper addresses the problem of accounting for graded
data in linguistic theory. As a model for graded grammaticality,
we propose an extended version of Optimality Theory, relying
on the concept of ranked grammatical constraints that is
independently motivated in Optimality Theory. In this model,
the ranking of constraints induces a ranking of linguistic
structures, and degrees of grammaticality emerge as a property
of suboptimal structures. We show in detail how this framework
can be used to account for extraction from picture NPs based
on graded experimental data.

Comments: In Alexis Dimitriadis, Laura Siegel, Clarissa Surek-Clark, and Alexander Williams, eds., Proceedings of the 21st Annual Penn Linguistics Colloquium, 169-186. Philadelphia, 1997.
Keywords: extraction, gradience, magnitude estimation, picture nouns
Areas: Psycholinguistics,Syntax
Type: Conference Proceedings Chapter

Direct link: http://roa.rutgers.edu/view.php3?roa=672