The µ-TBL Homepage

Tools for Transformation-Based Learning

Introduction

The µ-TBL system represents an attempt to use the search and database capabilities of the Prolog programming language to implement a generalized form of transformation-based learning. The µ-TBL system is designed to be:

General: The system supports four types of transformational operators (four types of rules) by means of which not only traditional ‘Brill-taggers’, but also Constraint Grammar disambiguators, are possible to train.
Easily extensible: Through its support of a compositional rule/template formalism and ‘pluggable’ algorithms, the system can easily be tailored to different learning tasks.
Efficient: A number of benchmarks have been run which show that the system is fairly efficient – an order of magnitude faster than Brill’s contextual-rule learner.

You may download papers and software, and there are example applications to experiment with. Send mail to torbjorn.lager@ling.gu.se if you want to be notified of further developments of the software.