Getting Real about Systematicity
Getting Real about Systematicity
This chapter empirically investigates the issue of systematicity and connectionism under more realistic conditions than was the case in previous studies. A connectionist and a symbolic model of sentence processing are compared on their ability to perform systematically. Both models are trained on over 700,000 sentences, and tested on 361 sentences, from naturally occurring texts. Although the symbolic model does display slightly stronger systematicity, there is a striking similarity between the two models’ performance. It is argued that real-world tasks pose such strong demands and constraints that performance cannot differ much across models. Consequently, the issue of systematicity loses much of its relevance.
Keywords: Connectionist and symbolic models, Sentence processing, Computational linguistics, Systematicity, Real-world constraints
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