Proceedings of the Annual Meeting of the Cognitive Science Society

Existing models of sentence comprehension typically adopt a deterministic approach that decides on the correct parse of a sentence. In essence, these models consist of algorithms that statically capture a priori rules for disambiguation and seldom take into account the context of interpretation. Also, their deterministic nature eliminates the possibility of recognizing a genuine ambiguity. We argue that the very essence of the quantitative model of memory we have developed, that is, its time-constrained nature, allows for a non- deterministic contextual approach to structural disambiguation. In this paper, w e focus specifically on the problem of PP (Prepositional Phrase) Attachment. More precisely, w e contend that a solution to this problem depends on the use of both a massively parallel time-constrained architecture and a quantitatively-defined context.