This report details research plans to extend work on hybrid deterministic parsing. The approach is hybrid in its combination of symbolic and sub-symbolic (connectionist) approaches. The research is investigating (1) new and more robust architectures for deterministic parsing which are hybrid mixtures of symbolic and sub-symbolic components, (2) combinations of syntax with lexical access and other components of natural language processing in order to determine how the distributed patterns of connectionism may enable better interfaces among these components, and (3) properties of the rules in the rule-based deterministic processing of natural language that make them most suitable for sub-symbolic training. Certainly, both symbolic and sub-symbolic components are important for language processing. This research is attempting to understand how best to make the division between the two types of components. Our goal is to provide insights from his perspective and to show that the two approaches, if appropriately combined, can mutually benefit each other. Furthermore, the development of representation techniques which encode ambiguity (rather than making arbitrary choices) is being examined as a useful methodological shift in dictating how systems can be decomposed into their parts. Various system architectures are being explored over a spectrum of symbolic and sub-symbolic arrangements. We are exploring the proper connections among the parts while integrating the components required for NLP. These systems are organized around syntax, but not exclusively limited to it. We want to achieve a better understanding of such systems and attain a clearer idea of which components are best accomplished symbolically and which ones sub-symbolically
