Unexpected Wide‐Scope Phenomena

Bibliographic Data

ID19079686
AuthorsEddy G Ruys, Bert Spector (0000-0003-0468-5986), Benjamin Spector
Year2017
Pages1-50
Publication date2017-11-07
Peer ReviewedYes
Open AccessYes
TypeOTHER
VenueThe Wiley Blackwell Companion to Syntax, Second Edition (JOURNAL)
PublisherWiley (PUBLISHER • GB)
DOI10.1002/9781118358733.wbsyncom089
OpenAlexW4246504801
ISBN9781118358733
LanguageEN
Citations received1
References cited29

It has long been known that quantificational expressions in natural language do not all have the same scope properties. While the scope of some expressions is closely related to their observable, “surface” position in syntactic structure, other expressions display a remarkable degree of freedom with respect to the relative scope that may obtain between them and other expressions in the structure. In generative syntax, the operation known as “quantifier raising” (QR) is responsible for cases where the scope of an operator does not correspond to its surface position. Because QR is itself subject to locality conditions, this approach predicts that departure from surface scope cannot exceed a certain syntactic distance. However, indefinites are able to take scope outside of the locality domain for QR (so‐called “scope island”). In order to preserve the advantages of a QR‐based theory of scope while at the same time accounting for the exceptional behavior of indefinites, a natural strategy has been either (i) to explain away the phenomenon of exceptional scope by showing it to be illusory, or (ii) to rely on an independent scopal mechanism in order to assign scope to the relevant indefinites, at least in certain configurations. Sophisticated approaches have been developed in syntax and formal semantics along such lines. This chapter aims to provide an overview of the current theoretical landscape regarding the scope of indefinites

Generative grammar · Linguistics · Locality · Programming language · Syntax · Computer Science · Natural Language Processing Techniques · Philosophy · Syntax, Semantics, Linguistic Variation · Artificial Intelligence

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