Livre: Palmer, Gildea, Xue: Semantic Role Labeling

[Thierry Hamon]

Date: Mon, 21 Jun 2010 17:22:48 -0400
From: Graeme Hirst <gh at cs.toronto.edu>
Message-Id: <968761A9-1344-4248-A3EF-C2A65AB06375 at cs.toronto.edu>
X-url: http://dx.doi.org/10.2200/S00239ED1V01Y200912HLT006


BOOK ANNOUNCEMENT

Semantic Role Labeling

Martha Palmer (University of Colorado, Boulder)
Daniel Gildea (University of Rochester)
Nianwen Xue (Brandeis University)

Synthesis Lectures on Human Language Technologies #6 (Morgan &
Claypool Publishers), 2010, 103 pages

Abstract

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

http://dx.doi.org/10.2200/S00239ED1V01Y200912HLT006


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