This paper defends a principle-based model of sen- tence processing, and demonstrates that such a model must have two specific properties: (1) it must use a partially top-down parsing mechanism, possibly re- stricted to functional structure, and (2) it must use an Active Trace Strategy, which freely posits traces before their linear string position. It is argued that both of the proposed mechanisms follow from an over- arching Principle of Incremental Comprehension.

We investigate the explanatory power of very simple statistical mechanisms within a modular model of the Human Sentence Processing Mechanism. In particular, we borrow the idea of a 'part-of-speech tagger' from the field of Naniral Language Processing, and use this to explain a number of existing experimental results in the area of lexical category disambiguation. Not only can each be explained without the need to posit extra mechanisms or constraints, but the exercise also suggests a novel account for some established data.