A Propositional Semantic Network with Structured Variables for Natural Language Processing

This paper suggests some goals for knowledge representation for natural language processing: natural form, conceptual completeness, structure sharing. To address these goals, an augmentation to the representation of variables so that variables are not atomic terms is suggested. This leads to an extended, more \natural" representation language whose use and representations are consistent with the use of variables in natural language. It is shown how this representation simpli es the representation and use of complex noun phrases and resolves some representational di culties with sentences involving nonlinear quanti er scoping, in particular, donkey sentences.