Automatically generating natural language reports

Abstract

In this paper, we describe a system which generates natural language status reports for a set of inter-related processes at various stages of progress. The system has three modules—a rule-based domain knowledge representation module, and elaborate text planning module, and a surface generation module. The knowledge representation module models a set of processes that are encountered in a typical office environment, using a body of production rules which are explicitly sequenced using an augmented Petri net mechanism. The system employs an interval-based temporal network for storing historical information. A text planning module traverses this network to search for events which need to be mentioned in a coherent report describing the current status of the system. The planner combines similar information for succinct presentation whenever applicable. It also employs discourse focus techniques and a simple notion of view transforms for the generation of good quality text. Finally, an available surface generation module which has been suitably augmented is used to produce well-structured textual reports for our chosen domain.