Natural language processing tools and environments: the field in perspective

Abstract

Tools and environments for natural language processing (NLP) originated approximately four decades ago with dictionary-based machine translation systems. When examining the evolution of the field, one observes a transition from these "embryonic" systems of the fifties to the more adaptable, robust, and user-friendly environments of the nineties. Currently, the state-of-the-art in such systems is based on a wide variety of linguistic theories, cognitive models, and engineering approaches. The paper looks briefly at the tools and environments available today.<>