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Resolving ambiguous polarity stripping ellipsis structures in Persian

Bibliographic Data

ID22130605
AuthorsVahideh Rasekhi (UCLA Health), Jesse Harris (0000-0001-7222-8344, University of California, Los Angeles)
Year2021
Volume6
Issue1
Publication date2021-10-07
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGlossa a journal of general linguistics (JOURNAL)
Journal identifiersISSN: 2397-1835 • E-ISSN: 2397-1835
PublisherOpen Library of the Humanities (PUBLISHER)
DOI10.16995/glossa.5881
OpenAlexW3204965060
LanguageEN
Citations received1
References cited54

Previous studies have shown that English speakers use a range of factors including locality, information structure, and semantic parallelism to interpret clausal ellipsis structures. Yet, the relative importance of each factor is currently underexplored. As cues to information structure and semantic parallelism are often implicit in English, we turned to Persian which marks information structure overtly via word order scrambling and uses the -rā morpheme to indicate definiteness/specificity on direct objects. To determine what strategies Persian speakers use to disambiguate clausal ellipsis, we conducted a naturalness rating study and sentence completion task on polarity stripping structures. Our results show that information structure and parallelism strongly influence correlate resolution in both tasks, but that a weaker preference for a local correlate emerges in scrambling in the sentence completion task. As these results diverge from those obtained in English studies, we speculate that the morphosyntactic properties of Persian constrain the strategies the processer uses in selecting a contrastive correlate and resolving ambiguity in stripping ellipsis

Ambiguity · Ambiguity Resolution · Information Structure · Linguistics · Natural language processing · Sentence · Turkish · Cognitive and developmental aspects of mathematical skills · Computer Science · Reading and Literacy Development · Syntax, Semantics, Linguistic Variation · Artificial Intelligence

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Unique citing works1
Citations per year0,33
Citation span2023 - 2023 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1
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