Incremental pragmatic interpretation of gradable adjectives: The role of standards of comparison

S. Alexandropoulou, Henrik Discher, Marisha Herb, Nicole Gotzner
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引用次数: 1

Abstract

While for relative gradable adjectives the value on the underlying measurement scale that serves as a standard of comparison is contextually determined, for absolute gradable adjectives this is typically taken to be a fixed, context-invariant value (Rotstein & Winter 2004; Kennedy & McNally 2005). The present study investigates how lexical-semantic factors, such as the type of standard of comparison invoked by gradable adjectives, affect the incremental computation of scalar implicatures triggered by such adjectives. Our study shows that the incremental computation of scalar implicatures is facilitated by the immediate visual context but only for relative adjectives. Minimum standard absolute adjectives, which impose a lower bound on their corresponding measurement scales, robustly trigger upper-bounded interpretations independently of the availability of contrastive visual information. Our findings indicate that different kinds of scalar meaning are computed incrementally and potentially in parallel. Overall, these findings shed new light on theories of scalar implicatures and highlight the need for a model of adjective meaning that incorporates semantic and pragmatic factors (see also Gotzner 2021; and for related ideas in the domain of quantifiers see Franke & Bergen 2020 and Cremers, Wilcox & Spector 2022, and Magri (2017) for Hirschberg scales).
分级形容词的增量语用解释:比较标准的作用
相对可分级形容词作为比较标准的基础测量量表上的值是由上下文决定的,而绝对可分级形容词通常被认为是一个固定的、上下文不变的值(Rotstein & Winter 2004;Kennedy & McNally 2005)。本研究探讨了词汇语义因素,如可分级形容词所调用的比较标准类型,如何影响这些形容词所触发的标量含义的增量计算。我们的研究表明,标量含义的增量计算是由直接的视觉环境促进的,但仅适用于相对形容词。最小标准绝对形容词在其相应的测量尺度上施加了一个下界,它强有力地触发了独立于对比视觉信息可用性的上界解释。我们的研究结果表明,不同类型的标量含义是增量计算的,并且可能是并行计算的。总的来说,这些发现揭示了标量蕴涵理论的新亮点,并强调需要一个包含语义和语用因素的形容词意义模型(另见Gotzner 2021;量词领域的相关观点见Franke & Bergen 2020和Cremers, Wilcox & Spector 2022,以及Magri(2017)的Hirschberg量表)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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