Novice-Friendly Natural Language Generation Template Authoring Environment

Abstract

Natural Language Generation (NLG) systems can make data accessible in an easily digestible textual form; but using such systems requires sophisticated linguistic and sometimes even programming knowledge. We have designed and implemented an environment for creating and modifying NLG templates that requires no programming knowledge, and can operate with a minimum of linguistic knowledge. It allows specifying templates with any number of variables and dependencies between them. It internally uses SimpleNLG to provide the linguistic background knowledge. We test the performance of our system in the context of an interactive simulation game.