29.3686, Diss: Syntax; Text/Corpus Linguistics: William Dyer: ''Minimizing Integration Cost: A General Theory of Constituent Order''

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LINGUIST List: Vol-29-3686. Tue Sep 25 2018. ISSN: 1069 - 4875.

Subject: 29.3686, Diss:  Syntax; Text/Corpus Linguistics: William Dyer: ''Minimizing Integration Cost: A General Theory of Constituent Order''

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Date: Tue, 25 Sep 2018 12:00:40
From: William Dyer [wm.e.dyer at gmail.com]
Subject: Minimizing Integration Cost: A General Theory of Constituent Order

 
Institution: University of California, Davis 
Program: Department of Linguistics 
Dissertation Status: Completed 
Degree Date: 2017 

Author: William Dyer

Dissertation Title: Minimizing Integration Cost: A General Theory of
Constituent Order 

Dissertation URL:  https://ucdavis.app.box.com/s/h4yk2plex1f4ls7d99zf0myr8ttxlkjv

Linguistic Field(s): Syntax
                     Text/Corpus Linguistics


Dissertation Director(s):
John A. Hawkins
Raul Aranovich
Santiago Barreda

Dissertation Abstract:

A major question in linguistics is why words and phrases—more generally,
constituents—have preferred orders cross-linguistically, where ‘preferred’
covers both possible and probable. Why does ''the good Italian wine'' sound
better than ''the Italian good wine,'' or ''good Italian the wine''? Disparate
theories have been advanced to address different types of constituents, from
stacked attributive adjectives to postverbal prepositional phrases, though
many of these suffer from inaccuracy, lack of testability, or questionable
explanatory power.

This dissertation aims to fill this gap by advancing a general theory of
constituent ordering. Relying on a quantitative syntactic analysis within a
dependency-grammar framework, the study begins with the notion that the cost
of integrating dependents to their heads derives from two sources: the
complexity of the integration and the distance between dependent and head (cf.
Gibson, 1998; Gibson, 2000). While the distance-based part has been
convincingly addressed in the literature (cf. H. Liu, Xu, and Liang, 2017, for
an overview), the complexity part remains unresolved.

It is proposed that the complexity of the dependency relation can be measured
by the entropy of the distribution created by the probabilities of each
dependent’s heads. Aggregated across all constituents in a sequence, and
thereby capturing the distance cost of the integration as well, this combined
metric of Aggregate Complexity (AC) serves as a measure of processing
difficulty—and therefore integration cost—for a given constituent order. It is
hypothesized that the linearization which minimizes AC tends to represent the
preferred order of the underlying dependency structure.

To test the hypothesis, corpus data from 51 languages from the Universal
Dependencies project is analyzed in order to show that Aggregate Complexity
Minimization (ACM) effectively explains cross-linguistic regularities of
attested orders. The dissertation demonstrates how previous models can be
subsumed by or extended into ACM, as well as how compression links
constituent-order preferences with efficiency and ultimately more universal
principles.




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