LINGUIST List 14.694

Tue Mar 11 2003

Diss: Computational Ling: Fouvry "Robust..."

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  1. fouvry, Computational Ling: Fouvry "Robust Processing..."

Message 1: Computational Ling: Fouvry "Robust Processing..."

Date: Mon, 10 Mar 2003 12:02:35 +0000
From: fouvry <fouvrycoli.uni-sb.de>
Subject: Computational Ling: Fouvry "Robust Processing..."

Institution: University of Essex
Program: Department of Language and Linguistics
Dissertation Status: Completed
Degree Date: 2003

Author: Frederik Fouvry 

Dissertation Title: 
Robust Processing for Constraint-based Grammar Formalisms

Linguistic Field: Computational Linguistics

Dissertation Director 1: Doug J Arnold

Dissertation Abstract: 

This thesis addresses the issue of how Natural Language Processing
(NLP) systems using "constraint-based" grammar. Formalisms can be
made "robust," i.e. able to deal with input which is in some way
ill-formed or extra-grammatical. In NLP systems which use
constraint-based grammars the operation of "unification" typically
plays a central role. Accordingly, the central concern of this thesis
is to propose an approach to "robust unification."

The first part of the thesis underlines the importance of robustness
in NLP, provides an overview of the sort of phenomena that require it,
and reviews the state of the art. From this, it appears that no
methods currently exist for robust processing with grammars of any
real linguistic sophistication.

The class of constraint-based grammars studied here is that based on
Typed Feature Logic (TFL), of which Head-Driven Phrase Structure
Grammar is the instance chosen for exemplification. The formalism is
described in the second part of the thesis.

Grammars based on TFL involve the notion of a "signature," which
defines the kinds of objects ("types") assumed to exist in the
grammar. Processing typically involves combining information about
pieces of the input by unification. From this perspective, the need
for robustness can be seen as arising because pieces of the input
provide information which is inconsistent with information from other
pieces of the input and/or from the grammar. The first inconsistency
is tolerated --- it does not violate the grammar --- and processed
using "robust types" which are created by extending the signature to a
lattice. Inconsistency with the grammar on the other hand is punished
by stripping away the offending information. Weights, added to it on
the basis of the grammar, also disappear, thus making the
ungrammaticality measurable. The conceptual and formal apparatus for
this is developed and exemplified in the third part of the
dissertation.
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