Automatic semantic relation extraction from Portuguese texts

Nowadays we are facing a growing demand for semantic knowledge in computational applications, particularly in Natural Language Processing (NLP). However, there aren't sufficient human resources to produce that knowledge at the same rate of its demand. Considering the Portuguese language, which has few resources in the semantic area, the situation is even more alarming. Aiming to solve that problem, this work investigates how some semantic relations can be automatically extracted from Portuguese texts. The two main approaches investigated here are based on (i) textual patterns and (ii) machine learning algorithms. Thus, this work investigates how and to which extent these two approaches can be applied to the automatic extraction of seven binary semantic relations (is-a, part-of, location-of, effect-of, property-of, made-of and used-for) in Portuguese texts. The results indicate that machine learning, in particular Support Vector Machines, is a promising technique for the task, although textual patterns presented better results for the used-for relation.