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Glossa: a journal of general linguistics
Article . 2021 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Glossa: a journal of general linguistics
Article
License: CC BY
Data sources: UnpayWall
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Article . 2021
License: CC BY
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Null arguments and the inverse problem

Authors: Brattico, Pauli;

Null arguments and the inverse problem

Abstract

Native speakers can reconstruct null arguments from a linear string of words where they are notoriously absent. How they solve this problem remains an unsolved and largely unaddressed issue. This article argues for a unified analysis of null arguments that relies on bare sensory input. The key assumption is that antecedent recovery takes place at the syntax-semantics interface if and only if the unvalued phi-features of a lexical element cannot be valued from the information available in the sensory input. The analysis unifies the theory of finite null subject pronouns and control and furthermore interprets null argument sentences without generating phrasal null pronouns. Evidence is considered from three languages with distinct null argument profiles: English (non-pro drop), Italian (consistent pro-drop) and Finnish (partial prodrop). Finally, the model was formalized and tested by means of a computer simulation.

Keywords

computational linguistics, Language. Linguistic theory. Comparative grammar, P101-410, pro-drop, parsing, control, null arguments, language comprehension

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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!
0
Average
Average
Average
Green
gold