Neural Network Design for a Natural Language Parser

The pattern matching capabilities of neural networks can be mobilised for an automated, natural language, partial parser. First, language complexity is addressed by decomposing the problem into more tractable subtasks. Second, a representation is devised that enables effective, single layer networks to be used to map a pre-defined grammatic framework onto actual sentences. This paper examines data representation, network architecture and learning algorithms appropriate for linguistic data with their characteristic distributions. Users can access a working prototype via telnet on which they can try their own text.