Proceedings of the Annual Meeting of the Cognitive Science Society

Models of human parsing typically focus on explaining syntactic preferences and garden-path phenomena. This paper explores another aspect of the processing of syntactic ambiguity—the successful revision of previously preferred structure. In the competitive attachment model of parsing, a hybrid connectionist network directly represents the attachment structure among phrasal nodes in a parse tree. A syntactic ambiguity leads to a network of alternative attachments that compete for numeric activation. The winning attachments are determined within a parallel operation that simultaneously revises earlier attachments as needed when initially attaching a new phrase to the developing parse tree. Because of the unique parallel structuring operation, the competitive attachment model provides a unified explanation of human preference and recovery mechanisms in parsing. The paper demonstrates this ability by showing how the model accounts for recency effects in human syntactic processing. In the parsing network, a mechanism of decay, which is independently needed to manage the finite pool of processing nodes, allows more recent phrases to compete more effectively than less recent phrases for new attachments. The effect of decay on the attachment competition underlies a unified account of psycholinguistic observations of recency, both in initial syntactic preferences and in the revision of erroneous attachments.