  The development of models of human sentence processing has traditionally
followed one of two paths. Either the model posited a sequence of processing
modules, each with its own task-specific knowledge (e.g., syntax and
semantics), or it posited a single processor utilizing different types of
knowledge inextricably integrated into a monolithic knowledge base. Our
previous work in modeling the sentence processor resulted in a model in which
different processing modules used separate knowledge sources but operated in
parallel to arrive at the interpretation of a sentence. One highlight of this
model is that it offered an explanation of how the sentence processor might
recover from an error in choosing the meaning of an ambiguous word. Recent
experimental work by Laurie Stowe strongly suggests that the human sentence
processor deals with syntactic error recovery using a mechanism very much like
that proposed by our model of semantic error recovery. Another way to interpret
Stowe's finding is this: the human sentence processor consists of a single
unified processing module utilizing multiple independent knowledge sources in
parallel. A sentence processor built upon this architecture should at times
exhibit behavior associated with modular approaches, and at other times act
like an integrated system. In this paper we explore some of these ideas via a
prototype computational model of sentence processing called COMPERE, and
propose a set of psychological experiments for testing our theories.
