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The Computation of Verb-Argument Relations in Online Sentence Comprehension.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Computation of Verb-Argument Relations in Online Sentence Comprehension./
Author:	Liao, Chia-Hsuan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	227 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-04, Section: A.
Contained By:	Dissertations Abstracts International82-04A.
Subject:	Linguistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28027801
ISBN:	9798678124746

The Computation of Verb-Argument Relations in Online Sentence Comprehension.
Liao, Chia-Hsuan.

The Computation of Verb-Argument Relations in Online Sentence Comprehension. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 227 p.

Source: Dissertations Abstracts International, Volume: 82-04, Section: A.

Thesis (Ph.D.)--University of Maryland, College Park, 2020.

This item must not be sold to any third party vendors.

Understanding how verbs are related to their arguments in real time is critical to building a theory of online language comprehension. This dissertation investigates the incremental processing of verb-argument relations with three interrelated approaches that use the event-related potential (ERP) methodology. First, although previous studies on verb-argument computations have mainly focused on relating nouns to simple events denoted by a simple verb, here I show by investigating compound verbs I can dissociate the timing of the subcomputations involved in argument role assignment. A set of ERP experiments in Mandarin comparing the processing of resultative compounds (Kid bit-broke lip: the kid bit his lip such that it broke) and coordinate compounds (Store owner hit-scolded employee: the store owner hit and scolded an employee) provides evidence for processing delays associated with verbs instantiating the causality relation (breaking-BY-biting) relative to the coordinate relation (hitting-AND-scolding). Second, I develop an extension of classic ERP work on the detection of argument role-reversals (the millionaire that the servant fired) that allows me to determine the temporal stages by which argument relations are computed, from argument identification to thematic roles. Our evidence supports a three-stage model where an initial word association stage is followed by a second stage where arguments of a verb are identified, and only at a later stage does the parser start to consider argument roles. Lastly, I investigate the extent to which native language (L1) subcategorization knowledge can interfere with second language (L2) processing of verb-argument relations, by examining the ERP responses to sentences with verbs that have mismatched subcategorization constraints in L1 Mandarin and L2 English ("My sister listened the music"). The results support my hypothesis that L1 subcategorization knowledge is difficult for L2 speakers to override online, as they show some sensitivity to subcategorization violations in offline responses but not in ERPs. These data indicate that computing verb-argument relations requires accessing lexical syntax, which is vulnerable to L1 interference in L2. Together, these three ERP studies allow us to begin to put together a full model of the sub-processes by which verb-argument relations are constructed in real time in L1 and L2.

ISBN: 9798678124746Subjects--Topical Terms:

524476
Linguistics.
Subjects--Index Terms:

Argument structure

The Computation of Verb-Argument Relations in Online Sentence Comprehension.
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300 $a 227 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-04, Section: A.
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502 $a Thesis (Ph.D.)--University of Maryland, College Park, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Understanding how verbs are related to their arguments in real time is critical to building a theory of online language comprehension. This dissertation investigates the incremental processing of verb-argument relations with three interrelated approaches that use the event-related potential (ERP) methodology. First, although previous studies on verb-argument computations have mainly focused on relating nouns to simple events denoted by a simple verb, here I show by investigating compound verbs I can dissociate the timing of the subcomputations involved in argument role assignment. A set of ERP experiments in Mandarin comparing the processing of resultative compounds (Kid bit-broke lip: the kid bit his lip such that it broke) and coordinate compounds (Store owner hit-scolded employee: the store owner hit and scolded an employee) provides evidence for processing delays associated with verbs instantiating the causality relation (breaking-BY-biting) relative to the coordinate relation (hitting-AND-scolding). Second, I develop an extension of classic ERP work on the detection of argument role-reversals (the millionaire that the servant fired) that allows me to determine the temporal stages by which argument relations are computed, from argument identification to thematic roles. Our evidence supports a three-stage model where an initial word association stage is followed by a second stage where arguments of a verb are identified, and only at a later stage does the parser start to consider argument roles. Lastly, I investigate the extent to which native language (L1) subcategorization knowledge can interfere with second language (L2) processing of verb-argument relations, by examining the ERP responses to sentences with verbs that have mismatched subcategorization constraints in L1 Mandarin and L2 English ("My sister listened the music"). The results support my hypothesis that L1 subcategorization knowledge is difficult for L2 speakers to override online, as they show some sensitivity to subcategorization violations in offline responses but not in ERPs. These data indicate that computing verb-argument relations requires accessing lexical syntax, which is vulnerable to L1 interference in L2. Together, these three ERP studies allow us to begin to put together a full model of the sub-processes by which verb-argument relations are constructed in real time in L1 and L2.
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650 4 $a Language. $3 643551
650 4 $a Reading instruction. $3 2122756
653 $a Argument structure
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653 $a P600
653 $a Prediction
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