The Internet Archive has a preservation copy of this work in our general collections.
The file type is
This paper presents results from the first attempt to apply Transformation-Based Learning to a discourse-level Natural Language Processing task. To address two limitations of the standard algorithm, we developed a Monte Carlo version of Transformation-Based Learning to make the method tractable for a wider range of problems without degradation in accuracy, and we devised a committee method for assigning confidence measures to tags produced by Transformation-Based Learning. The paper describesarXiv:cmp-lg/9806007v1 fatcat:p4krwr3sgna4pinymq6vrou2hm