Constituency and Recursion in Language

artificial languages, Christiansen and Chater (1999) show that the SRN’s general pattern of performance is relatively invariant across network size and training corpus, and conclude that the human-like pattern of performance derive from intrinsic constraints inherent in the SRN architecture. Connectionist models of recursive syntax typically use “toy” fragments of grammar and small vocabularies. Aside from raising concerns over scalingup, this makes it difficult to provide detailed fits with empirical data. Nonetheless, some attempts have recently been made toward fitting existing data and deriving new empirical predictions from the models. For example, the Christiansen and Chater (1999) SRN model fits grammaticality ratings data from several behavioral experiments, including an account of the relative processing difficulty associated with the processing center-embeddings (with the following relationship between nouns and verbs: N1N2N3V3V2V1) vs. cross-dependencies (with the following relationship between nouns and verbs: N1N2N3V1V2V3). Human data have shown that sentences with two centerembeddings (in German) were significantly harder to process than comparable sentences with two cross-dependencies (in Dutch). The simulation results demonstrated that the SRNs exhibited the same kind of qualitative processing difficulties as humans on these two types of complex recursive constructions. Just as the radical connectionist approach to constituency deviates from classical constituency, the above approach to recursion deviates from the classical notion of recursion. The radical models of recursion do not acquire “true” recursion because they are unable to process infinitely complex recursive constructions. However, the classic notion of recursion may be illsuited for capturing human recursive abilities. Indeed, the psycholinguistic data suggest that people’s performance may be better construed as being only “quasi-recursive”. The earlier mentioned semantic facilitation of recursive processing further suggests that human recursive performance may be partially context-sensitive; for example, the semantically biased ‘The bees that the hive that the farmer built housed stung the children’ is easier to comprehend than neutral ‘The chef that the waiter that the busboy offended appreciated admired the musicians’ even though both sentences contain two center-embeddings. This dovetails with the context-sensitive notion of constituency, and suggests that context-sensitivity may be a more pervasive feature of language processing than typically assumed by symbolic approaches.