Susan Rothstein | Bar Ilan University, Gonda Multidisciplinary Brain Research
Center
Analysing aspects of how our brain processes
language may provide, even before the language faculty is really understood,
useful insights into higher order cognitive functions. We have taken initial
steps in this direction, focusing on the mass-count distinction. The
mass-count distinction relates to the countability or un-countability of
nouns in terms of their syntactic usage. Our first results show that the
mass-count distinction, across a number of natural languages, is far from
bimodal, and exhibits in fact complex fuzzy relations between syntax and
semantics. We then tried to test the ability of a standard, biologically
plausible self-organising neural network to learn such associations between
syntax and semantics. A neural network that expresses competition amongst
output neurons with lateral inhibition can identify the basic classes of
mass and count in the syntactic markers and produce a graded distribution of
the nouns along the mass-count spectrum. The network however fails to
successfully map the semantic classes of the nouns to their syntactic usage,
thus corroborating the hypothesis that the syntactic usage of nouns in the
mass-count domain is not simply predicted by the semantics of the noun.
(2013) A
statistical investigation into the cross-linguistic distribution of
mass and count nouns: Morphosyntactic and semantic
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(2016) A
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(2009) Computational
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(2017) Semantics
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Cited by
Cited by 1 other publications
Moltmann, Friederike
2022. Names, Light Nouns, and Countability. Linguistic Inquiry 54:1 ► pp. 117 ff.
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