SYSTEM DEMONSTRATION NATURAL LANGUAGE GENERATION WITH ABSTRACT MACHINE

We present a system for Natural Language Generation based on an Abstract Machine approach. Our abstract machine operates on grammars encoded in a unification-based Typed Feature Structure formalism, and is capable of both generation and parsing. For efficient generation, grammars are first inverted to a suitable form, and then compiled into abstract machine instructions. A dual compiler translates the same input grammar into an abstract machine program for parsing. Both generation and parsing programs are executed under the same (chart-based) evaluation strategy: This results in an efficient, bidirectional (parsing/generation) System for Natural Language Processing. Moreover, the system possesses ample debugging features, and thus can serve as a user-friendly environment for bidirectional grammar design and development.