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Semantic Role Labeling (Paperback)
Loot Price: R1,014
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Semantic Role Labeling (Paperback)
Series: Synthesis Lectures on Human Language Technologies
Expected to ship within 10 - 15 working days
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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. Table
of Contents: Preface / Semantic Roles / Available Lexical Resources
/ Machine Learning for Semantic Role Labeling / A Cross-Lingual
Perspective / Summary
General
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