عنوان

Semantic role labeling /

(Number (ISBN

1598298321

(Number (ISBN

9781598298321

Erroneous ISBN

1598298313

Erroneous ISBN

9781598298314

Number

b781666

Title Proper

Semantic role labeling /

General Material Designation

[Book]

First Statement of Responsibility

Martha Palmer, Daniel Gildea, Nianwen Xue.

Place of Publication, Distribution, etc.

[San Rafael, Calif.] :

Name of Publisher, Distributor, etc.

Morgan & Claypool Publishers,

Date of Publication, Distribution, etc.

©2010.

Specific Material Designation and Extent of Item

1 online resource (ix, 91 pages) :

Other Physical Details

illustrations (some color)

Series Title

Synthesis lectures on human language technologies,

Volume Designation

#6

ISSN of Series

1947-4040 ;

Text of Note

Includes bibliographical references (pages 79-89).

Text of Note

Semantic roles. Introduction -- Linguistic background -- More elaborated frameworks -- Available lexical resources. FrameNet -- VerbNet -- PropBank -- Semlink -- Summary -- 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 -- A cross-lingual perspective. Semantic role projection -- Semantic role alignment -- Language-(in)dependent semantic role labeling -- Summary. Bibliography -- Authors' biographies.

0

Text of Note

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.

Source for Acquisition/Subscription Address

Safari Books Online

Stock Number

CL0500000332

Title

Semantic role labeling.

International Standard Book Number

9781598298314

Computational linguistics.

Semantics.

Computational linguistics.

LANGUAGE ARTS & DISCIPLINES-- Linguistics-- Historical & Comparative.

Semantics.

LAN-- 009010

Number

Edition

Class number

Book number

Palmer, Martha Stone.

Gildea, Daniel.

Xue, Nianwen.

Date of Transaction

20201206202126.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y