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Experiments in Linguistic Meaning
Article . 2021 . Peer-reviewed
License: CC BY
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Pseudo-Incorporated Antecedents and Anaphora in Persian: The Influence of Stereotypical Knowledge

Authors: Fereshteh Modarresi; Manfred Krifka;

Pseudo-Incorporated Antecedents and Anaphora in Persian: The Influence of Stereotypical Knowledge

Abstract

There are different theories about the nature of pseudo-incorporated nouns (PINs), which feature a non-specific, number-neutral interpretation. For a proper analysis it is crucial to take their anaphoric potential into account. This paper investigates if and how PINs introduce discourse referents, with evidence from Persian, and which theory matches this behavior best. We report on experiments in which the stereotypical enrichment of the number-neutral interpretation was systematically varied with two types of biases — towards a singular or a plural interpretation — and in the neutral case, when such a bias is lacking. The results of the experiments are compatible with Krifka & Modarresi (2016), which considers PIN objects as dependent singular definites (similar to weak definites) within existential closure over an event variable.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
hybrid