Proceedings of the Annual Meeting of the Cognitive Science Society

This symposium examines certain fundamental assumptions about structural systematicity and semantic compositionality in language implicit in generative linguistic theory and often adopted uncritically in cognitive science research. Generative analyses have presupposed that most linguistic phenomena can be described in terms of highly general (and hence highly productive) rules of phonological, morphological, syntactic, or semantic combination. Idiosyncractic linguistic phenomena are either relegated to the lexicon or attributed to contextual effects and effectively ignored by the rule-based grammar. However, assumptions about regularity in language (and rule-governed analyses thereof) both originated and are currently maintained only by the examination of a small set of often artificial examples. Moreover, the idealization away from performance data, that is, actual language use, tends to make linguistic rules seem more general and exceptionless than they turn out to be. Studies that involve exhaustive examination of the range of words or constructions to which a particular rule applies demonstrate that there are serious empirical problems with the general-rule approach. Constructions to which general rules are alleged to apply are in fact subtly idiosyncratic. O n the other hand, there are lowlevel regularities often overlooked by generative accounts that merit theoretical attention. The symposium participants will present perspectives on the study of language by cognitive linguists and connectionists, who take an exemplar-based approach to extracting regularity from Unguistic phenomena, revealing in the process that certain "irregularities" in language are in fact due to nonprototypicality. The panelists will illustrate the underspecificity, contextsensitivity, partial systematicity and partial compositionality of language, as evidenced in analyses of data at various linguistic levels. The discussion which follows will focus on ways in which computational models of language representation or processing might proceed without embracing assumptions of complete systematicity or perfect compositionality. Network models, in particular, seem to be highly compatib