Author_Institution :
Depts. of Linguistics & Comput. Sci., Purdue Univ., West Lafayette, IN, USA
Abstract :
Summary form only given. As the fear of semantics is declining, let´s formalize the unformalizable! The address is focusing on the feasibility and necessity of accessing directly the comprehensive meaning of natural language texts, data, images, etc., to emulate human understanding by the computer. It is based on the premise that, without such understanding, no real-life application can reach the precision that human users of computational systems require. Moreover, meaning access and processing goes well beyond natural language applications, even as the scope of those keeps growing. The main obstacle for this seemingly reasonable goal is the widespread prejudice against meaning as unknowable in principle because it is “subjective,” context-sensitive, complex, messy, etc. This has not been our experience, and it is worth talking, both practically and theoretically, about the know-how that a research group should acquire to approach the processing tasks semantically. A convincing case can be made for the feasibility and affordability of the approach as well, especially in the light of our planning to make our resources Open Source, a plan that may be followed by other computational semanticists. It is hoped, therefore, that this address will further reduce the fear of, and prejudice against semantics. It will focus on our Ontological Semantic Technology, a mature formal theory of meaning that has long overcome the crippling fixation on first-order logic as the only possible formalism for everything. This fixation has prevented generations of researchers to access natural language meaning to the grain size that makes meaning representation usable, both theoretically and in practical applications. A small set of predicates using a smaller number of variables as arguments may work well for formal languages but natural language defeats such an approach. The fear of semantics is based on the faulty conclusion that, therefore, natural language meaning is - ot formalizable. Throw away an insufficient method, and the task becomes feasible!
Keywords :
natural language processing; ontologies (artificial intelligence); comprehensive meaning; computational semanticists; computational systems; crippling fixation; first order logic; formal theory; human understanding; natural language applications; natural language meaning; natural language texts; ontological semantic technology; real-life application; Computational linguistics; Educational institutions; Information security; Natural language processing; Pragmatics; Semantics;