On Natural Language Generation of Formal Argumentation
This addresses the challenge of making formal argumentation systems accessible to users without extensive training, though it is an incremental step as it builds on preliminary studies.
The paper tackles the problem of communicating formal argumentation models to humans through natural language interfaces, finding that existing methods like graphical models require significant training and are ineffective, and proposes natural language as a promising alternative.
In this paper we provide a first analysis of the research questions that arise when dealing with the problem of communicating pieces of formal argumentation through natural language interfaces. It is a generally held opinion that formal models of argumentation naturally capture human argument, and some preliminary studies have focused on justifying this view. Unfortunately, the results are not only inconclusive, but seem to suggest that explaining formal argumentation to humans is a rather articulated task. Graphical models for expressing argumentation-based reasoning are appealing, but often humans require significant training to use these tools effectively. We claim that natural language interfaces to formal argumentation systems offer a real alternative, and may be the way forward for systems that capture human argument.