The need for robust and easily extensible systems for word sense disambiguation coupled with successes in training systems for a variety of tasks using large on-line corpora has led to extensive research into corpus-based statistical approaches to this problem. Promising…

Investigamos la posibilidad de obtener patrones semánticos a gran escala para cualquier lengua usando solamente análisis superficial y generalizaciones semánticas básicas. Siendo este un experimento exploratorio sólo hemos realizado una evaluación cualitativa. Hemos comparado varios patrones semánticos de traducción de…

We have developed a method and prototype program for assisting two experts in their attempts to construct a single, consensus knowledge base. We show that consensus building can be effectively facilitated by a debugging approach that identifies, explains, and resolves…

Most Natural Language Processing (NLP) systems traditionally use a sequential architecture that represents the classical linguistic levels (lexical-morphological, syntactical, semantic, etc.), but they claim for huge and monolithic modules, that make the backtracking among such modules difficult. By using a…

This paper examines the issues and the solutions that have been studied in database (DB) integration research and tries to draw lessons from them for knowledge base (KB) integration.

This paper deals with the "Calculus of Knowledge", an extension of the propositional calculus in which one may reason about what other people know. Semantic and Syntactic systems are developed, certain theorems are proven, and a formal solution in the…

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts…

Trying to capture intuitive knowledge is a little like trying to capture the moment between what just happened and what is about to happen. Or to quote a famous philosopher, "You can't put your foot in the same river once."…

This paper focuses on the general problem of the lexical bottleneck and, in particular, on the issues of semantic clustering and disambiguation by means of word usage cues obtained from sublanguage-specific corpora. Our approaches combines the use of numerical techniques…

This paper analyzes the suitability of reinforcement learning (RL) for both programming and adapting situated agents. We discuss two RL algorithms: Q-learning and the Bucket Brigade. We introduce a special case of the Bucket Brigade, and analyze and compare its…