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- W4386828183 abstract "Abstract This chapter provides an overview of some ways to bring evidence from experimental language-processing work to bear on theories of syntax, where the relevant syntactic theories are formulated as explicit, self-contained formal grammars. The focus is on linking hypotheses that take the form of complexity metrics, at differing levels of abstraction. At one level are information-theoretic metrics such as surprisal and entropy reduction, where a grammar’s role is to define a probability distribution over generated expressions; a key point emphasized here is the way a grammar’s generative mechanisms constrain the shapes of these distributions. At a lower, explicitly algorithmic, level of abstraction are metrics based on the memory load incurred by particular parsing algorithms. The concluding section outlines applications of these ideas to modern syntactic theory." @default.
- W4386828183 created "2023-09-19" @default.
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- W4386828183 date "2023-09-18" @default.
- W4386828183 modified "2023-09-29" @default.
- W4386828183 title "Formal Methods in Experimental Syntax" @default.
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- W4386828183 doi "https://doi.org/10.1093/oxfordhb/9780198797722.013.13" @default.
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