An edition of Semantic role labeling (2010)

Semantic role labeling

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Last edited by MARC Bot
January 3, 2023 | History
An edition of Semantic role labeling (2010)

Semantic role labeling

This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented.

Publish Date
Language
English

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Previews available in: English

Edition Availability
Cover of: Semantic role labeling
Semantic role labeling
2010, Morgan & Claypool Publishers
electronic resource / in English

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Book Details


Table of Contents

1. Semantic roles
Introduction
Linguistic background
More elaborated frameworks
2. Available lexical resources
FrameNet
VerbNet
PropBank
Semlink
Summary
3. Machine learning for semantic role labeling
Identification and classification
Features used for classification
Choice of machine learning method
Joint inference
Impact of parsing
Evaluation
Genre
Choice of resources and combination of resources
Unsupervised and partially supervised approaches
4. A cross-lingual perspective
Semantic role projection
Semantic role alignment
Language-(in)dependent semantic role labeling
5. Summary
Bibliography
Authors' biographies.

Edition Notes

Part of: Synthesis digital library of engineering and computer science.

Title from PDF t.p. (viewed on February 16, 2010).

Series from website.

Includes bibliographical references (p. 79-89).

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

Published in
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Series
Synthesis lectures on human language technologies -- # 6
Other Titles
Synthesis digital library of engineering and computer science.

Classifications

Dewey Decimal Class
410.285
Library of Congress
P98 .P257 2010, P325 .P35 2010

The Physical Object

Format
[electronic resource] /

Edition Identifiers

Open Library
OL25542630M
Internet Archive
semanticrolelabe00palm
ISBN 13
9781598298321, 9781598298314
OCLC/WorldCat
317114538

Work Identifiers

Work ID
OL16934540W

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
January 3, 2023 Edited by MARC Bot import existing book
June 18, 2022 Edited by ImportBot import existing book
February 25, 2022 Edited by ImportBot import existing book
May 17, 2020 Edited by CoverBot Added new cover
July 28, 2014 Created by ImportBot Imported from Internet Archive item record