Rasmussen Nathan E, Schuler William
Department of Linguistics, The Ohio State University.
Cogn Sci. 2018 Jun;42 Suppl 4:1009-1042. doi: 10.1111/cogs.12511. Epub 2017 Aug 1.
This article describes a left-corner parser implemented within a cognitively and neurologically motivated distributed model of memory. This parser's approach to syntactic ambiguity points toward a tidy account both of surprisal effects and of locality effects, such as the parsing breakdowns caused by center embedding. The model provides an algorithmic-level (Marr, 1982) account of these breakdowns: The structure of the parser's memory and the nature of incremental parsing produce a smooth degradation of processing accuracy for longer center embeddings, and a steeper degradation when they are nested, in line with recall observations by Miller and Isard (1964) and speed-accuracy trade-off observations by McElree et al. (2003). Modeling results show that this effect is distinct from the effects of ambiguity and exceeds the effect of mere sentence length.
本文描述了一种在基于认知和神经学的分布式记忆模型中实现的左角解析器。该解析器处理句法歧义的方法为意外效应和局部效应提供了一个简洁的解释，比如由中心嵌入导致的解析故障。该模型从算法层面（Marr，1982）对这些故障进行了解释：解析器记忆的结构以及增量解析的性质导致，对于更长的中心嵌入，处理精度会平稳下降；当它们嵌套时，精度下降得更快，这与Miller和Isard（1964）的回忆观察结果以及McElree等人（2003）的速度-准确性权衡观察结果一致。建模结果表明，这种效应与歧义效应不同，且超过了单纯句子长度的影响。
