LINGUIST List 17.1429|
Tue May 09 2006
Diss: Computational Ling: Poria: 'An Engineering App...'
Editor for this issue: Meredith Valant
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An Engineering Approach to Knowledge Acquisition by the Interactive Analysis of Dictionary Definitions
Message 1: An Engineering Approach to Knowledge Acquisition by the Interactive Analysis of Dictionary Definitions
From: Sanjay Poria <sanjayporiahotmail.com>
Subject: An Engineering Approach to Knowledge Acquisition by the Interactive Analysis of Dictionary Definitions
Institution: University of Durham
Program: Department of Computer Science
Dissertation Status: Completed
Degree Date: 1998
Author: Sanjay Poria
Dissertation Title: An Engineering Approach to Knowledge Acquisition by the Interactive Analysis of Dictionary Definitions
Subject Language(s): None ()
It has long been recognised that everyday dictionaries are a potential
source of lexical and world knowledge of the type required by many Natural
Language Processing (NLP) systems. This research presents a semi-automated
approach to the extraction of rich semantic relationships from dictionary
definitions. The definitions are taken from the recently published
'Cambridge International Dictionary of English' (CIDE). The thesis
illustrates how many of the innovative features of CIDE can be exploited
during the knowledge acquisition process.
The approach introduced in this thesis uses the LOLITA NLP system to
extract and represent semantic relationships, along with a human operator
to resolve the different forms of ambiguity which exist within dictionary
definitions. Such a strategy combines the strengths of both participants in
the acquisition process: automated procedures provide consistency in the
construction of complex and inter-related semantic relationships, while the
human participant can use his or her knowledge to determine the correct
interpretation of a definition.
This semi-automated strategy eliminates the weakness of many existing
approaches because it guarantees feasibility and correctness: feasibility
is ensured by exploiting LOLITA's existing NLP capabilities so that humans
with minimal linguistic training can resolve the ambiguities within
dictionary definitions; and correctness is ensured because incorrectly
interpreted definitions can be manually eliminated.
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