Contextual Reasoning and Inferential Processing

The topic of this paper is the theoretical foundations and the results of a system for text analysis and understanding called GETA_RUN, developed at the University of Venice, Laboratory of Computational Linguistics, Institute of Linguistics and Language Teaching Theory. The main tenet of the theory supporting the construction of the system is that it is possible to reduce access to domain world knowledge by means of contextual reasoning, i.e. reasoning triggered independently by contextual or linguistic features of the text. Understanding a text requires a complete linguistic analysis. This may be geared onto inferential processes needed to make explicit knowledge of the world which is otherwise non linguistically expressed. It is sensible to assume that when understanding a text a human reader or listener does make use of his encyclopaedia parsimoniously. Contextual reasoning is the only way in which a system for Natural Language Understanding should tap external knowledge of the domain. In other words, a system should be allowed to perform an inference on the basis of domain world knowledge when needed and only then. In this way, the system could simulate the actual human behaviour in that the access to extralinguistic knowledge is triggered by contextual factors independently present in the text and detected by the system itself.