  Psychological investigations have led to considerable insight into the
working of the human language comprehension system. In this article, we look at
a set of principles derived from psychological findings to argue for a
particular organization of linguistic knowledge along with a particular
processing strategy and present a computational model of sentence processing
based on those principles. Many studies have shown that human sentence
comprehension is an incremental and interactive process in which semantic and
other higher-level information interacts with syntactic information to make
informed commitments as early as possible at a local ambiguity. Early
commitments may be made by using top-down guidance from knowledge of different
types, each of which must be applicable independently of others. Further
evidence from studies of error recovery and delayed decisions points toward an
arbitration mechanism for combining syntactic and semantic information in
resolving ambiguities. In order to account for all of the above, we propose
that all types of linguistic knowledge must be represented in a common form but
must be separable so that they can be applied independently of each other and
integrated at processing time by the arbitrator. We present such a uniform
representation and a computational model called COMPERE based on the
representation and the processing strategy.
