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The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing./
Author:	Jaffe, Evan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	131 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-06, Section: A.
Contained By:	Dissertations Abstracts International83-06A.
Subject:	Language. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28889433
ISBN:	9798492755607

The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing.
Jaffe, Evan.

The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 131 p.

Source: Dissertations Abstracts International, Volume: 83-06, Section: A.

Thesis (Ph.D.)--The Ohio State University, 2021.

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

Coreference resolution is an essential component of language comprehension that allows interlocutors to correctly identify who did what to whom and to quickly and accurately agree on a common way to point out concepts in a shared space. It offers insights into human cognition as it both recruits memory usage and implicates expectation, or anticipatory processing. This thesis explores coreference resolution as a cognitive process and models it with both (1) an incremental parser meant to model expectation and (2) an entity repetition-based measure designed to probe memory. The novel parsing model presented here jointly models word generation with structural decisions including coreference. Empirical results from reading, eye-tracking and brain imaging studies all point to an important role for coreference in online human sentence processing early in the time-course. Furthermore, comparison to contemporary neural network language models shows a dissociation between simple word predictability and goodness-of-fit to human processing. Creating a human-like model of sentence processing is not simply a matter of predicting the next word well, but also of capturing the contextual information that humans are sensitive to, including non-local semantic relations like coreference, and the relative uncertainty of upcoming material.

ISBN: 9798492755607Subjects--Topical Terms:

643551
Language.
Subjects--Index Terms:

Coreference

The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing.
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245 1 4 $a The Role of Coreference Resolution in Memory- and Expectation-Based Models of Human Sentence Processing.
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300 $a 131 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-06, Section: A.
500 $a Advisor: Schuler, William.
502 $a Thesis (Ph.D.)--The Ohio State University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Coreference resolution is an essential component of language comprehension that allows interlocutors to correctly identify who did what to whom and to quickly and accurately agree on a common way to point out concepts in a shared space. It offers insights into human cognition as it both recruits memory usage and implicates expectation, or anticipatory processing. This thesis explores coreference resolution as a cognitive process and models it with both (1) an incremental parser meant to model expectation and (2) an entity repetition-based measure designed to probe memory. The novel parsing model presented here jointly models word generation with structural decisions including coreference. Empirical results from reading, eye-tracking and brain imaging studies all point to an important role for coreference in online human sentence processing early in the time-course. Furthermore, comparison to contemporary neural network language models shows a dissociation between simple word predictability and goodness-of-fit to human processing. Creating a human-like model of sentence processing is not simply a matter of predicting the next word well, but also of capturing the contextual information that humans are sensitive to, including non-local semantic relations like coreference, and the relative uncertainty of upcoming material.
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650 4 $a Standard deviation. $3 3560390
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650 4 $a Magnetic resonance imaging. $3 554355
650 4 $a Reading. $3 516229
650 4 $a Semantics. $3 520060
653 $a Coreference
653 $a Surprisal
653 $a Psycholinguistics
653 $a Sentence processing
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