SGML-Based Markup as a Step toward Improving Knowledge Acquisition for Text Generation

Applying Machine Learning to Discourse Processing

Volume

Papers from the 1998 AAAI Spring Symposium

Contents

We are investigating computer-assisted methods for identifying plan operators at both the conversational strategy and surface generation levels. We are using standard-conforming SGML markup on our corpus in order to be able to process it mechanically. We are using C4.5 to identify rules of the form "when is goal x implemented with plan y?". We are currently testing these methods in the knowledge acquisition process for the text generation component of C1RCSIM-Tutor v. 3, a natural-language based intelligent tutoring system.