An Evaluation Framework for Controlled Natural Languages

Abstract. This paper presents a general framework called ontographs that relies on a graphical notation and enables the tool-independent and reliable evaluation of human understandability of knowledge represen-tation languages. An experiment with 64 participants is presented that applies this framework and compares a controlled natural language to a common formal language. The results show that the controlled natural language is easier to understand, needs less learning time, and is more accepted by its users.