Using Lexical Semantics to Predict the Distributivity Potential of Verb Phrases in a Large Dataset

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dc.contributor.author Glass, Lelia
dc.date.accessioned 2019-07-31T13:08:47Z
dc.date.available 2019-07-31T13:08:47Z
dc.date.issued 2019-07-31
dc.identifier.other 167210713X de_DE
dc.identifier.uri http://hdl.handle.net/10900/91245
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-912456 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-32626
dc.description.abstract Applied to a plural subject (“Alice and Bob”), some predicates are understood distributively (individually true of each member of the subject: “Alice and Bob smiled” conveys that Alice smiled and Bob smiled); some are understood nondistributively (true of the subject as a whole, but not each member individually: “Alice and Bob met”); and some can be understood in both ways (“Alice and Bob opened the window”: distributive if they each individually opened it, nondistributive if they opened it jointly). This paper tackles the open question of which predicates are understood in which way(s) and why: Which other predicates act like “smile”, like “meet”, or like “open the window”? Researchers would agree that a verb phrase's distributivity potential depends on world knowledge about the event that it describes. Making that truism predictive, this paper presents an experimental study providing evidence consistent with several large-scale, theoretically-motivated generalizations in this realm. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.classification Kausativ , Korpus <Linguistik> de_DE
dc.subject.ddc 400 de_DE
dc.subject.ddc 420 de_DE
dc.subject.other distributivity en
dc.subject.other causatives en
dc.subject.other experiments en
dc.subject.other corpus en
dc.title Using Lexical Semantics to Predict the Distributivity Potential of Verb Phrases in a Large Dataset en
dc.type ConferenceObject de_DE
utue.publikation.fachbereich Allgemeine u. vergleichende Sprachwissenschaft de_DE
utue.publikation.fakultaet 5 Philosophische Fakultät de_DE
utue.opus.portal ProcLingEvi2018 de_DE

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