  We present a knowledge and context-based system for parsing and translating
natural language and evaluate it on sentences from the Wall Street Journal.
Applying machine learning techniques, the system uses parse action examples
acquired under supervision to generate a deterministic shift-reduce parser in
the form of a decision structure. It relies heavily on context, as encoded in
features which describe the morphological, syntactic, semantic and other
aspects of a given parse state.
