Automatic Question Categorization: a New Approach for Text Elaboration Categorización automática de preguntas: un nuevo enfoque para elaboración de textos

Text adaptation is a normal activity of teachers to facilitate reading comprehension of specific contents; the general approaches for it are Text Simplification and Text Elaboration (TE). TE aims at clarifying, explaining information and making connections explicit in texts. In this paper, we present a new approach for TE: an automatic question categorization system which assigns wh-question labels to verbal arguments in a sentence. For example, in “Mary danced yesterday.” “Who?” is the label linking the verb “danced” to the argument “Mary” and “When?” links “danced” to the argument “yesterday”. This annotation is similar to semantic role labeling, approached successfully via statistical language processing techniques. Specifically, we present experiments to build the system using a fine-grained question set in Portuguese language and address two key research questions: (1) Which machine-learning algorithm presents the best results? (2) Which problems this task presents and how to overcome them?