The paper “TAF Language and Games for Story Comprehension” by Rosella Gennari, Sara Tonelli and Pierpaolo Vittorini has been accepted at Digital Intelligence 2014, the First International Scientific and Interdisciplinary Conference dedicated to digital society and cultures.
Developing the capabilities of all children to read and comprehend texts is fundamental for their development and full participation in society. Nowadays, a number of children lag behind their peers in text comprehension. TERENCE, an FP7 European project, considered this problem and created the first adaptive system for text comprehension for primary school children. At the core of the system is a mark-up language for story comprehension. The language is used for automatically annotating digital stories and generating components of digital games, mixing natural language processing and constraint-based technologies. This paper presents how the language was designed for annotating key features for story comprehension, and how it was used in TERENCE for generating digital games for story comprehension.