Graded Unification: A Framework for Interactive Processing

An extension to classical unification, called graded unification is presented. It is capable of combining contradictory information. An interactive processing paradigm and parser based on this new operator are also presented. Introduction Improved understanding of the nature of knowledge used in human language processing suggests the feasibility of interactive models in computational linguistics (CL). Recent psycholinguistic work such as (Stowe, 1989; Trueswell et al., 1994) has documented rapid employment of semantic information to guide human syntactic processing. In addition, corpus-based stochas-tic modelling of lexical patterns (see Weischedel et al., 1993) may provide information about word sense frequency of the kind advocated since (Ford et al., 1982). Incremental employment of such knowledge to resolve syntactic ambiguity is a natural step towards improved cognitive accuracy and efficiency in CL models. This exercise will, however, pose difficulties for the classical ('hard') constraint-based paradigm. As illustrated by the Trueswell et al. (1994) results, this view of constraints is too rigid to handle the kinds of effects at hand. These experiments used pairs of locally ambiguous reduced relative clauses such as: