Graduiertenkolleg ILS,
Seminar für Sprachwissenschaft,
Universität Tübingen,
Wilhelmstr. 133,
72074 Tübingen,
Germany,
phone: ++49 7071 2972732
e-mail:
riezler@sfs.nphil.uni-tuebingen.de(riezler@sfs.nphil.uni-tuebingen.de)
,
Supervisors
Prof. Dr. Erhard Hinrichs
Dr. Steven Abney
Preliminary Title
Probabilistic Constraint Logic Programming:
Formal Foundations and Applications to Natural Language Grammars
Abstract
Constraint logic grammars provide a powerful formalism for complex logical
descriptions of natural language phenomena in exact terms.
Describing some of these phenomena may, however, run
counter to the restrictive exactness of classical logics and instead
require some form of graded distinctions which are not provided by such
grammars.
Since the advent of statistical methods in computational
linguistics, much work has been done on probabilistic versions of regular and
context-free grammars. In addition to many other applications, these
approaches provide graded distinctions, e.g., for the general problem of
ambiguity resolution. Here probabilistic parameters can be automatically
estimated from natural language corpora and allow to distinguish parses by
their respective probabilities. Parsing can be speeded up by pruning low
probability subparses.
The aim of this thesis is to apply some of these methods to the framework of
highly expressive constraint logic grammars such as those underlying HPSG.
On the one hand, we want to maintain the formal semantic basis of
constraint logic grammars.
The key in this context is to provide a formal semantics for weighted
constraint logic grammars in a framework quantitative constraint logic
programming.
On the other hand, we want to develop on this basis a framework
for probabilistic constraint logic grammars. The key in this context is to
define a probabilistic model for constraint logic programming which allows
for automatic parameter estimation and best-parse search.