Experimental Investigations of Verification Procedures for Quantified Statements

数量表达，如EVERY，SOME，MOST，MOTHAN HALF等，在语言的科学研究中起着核心作用，因为它们引入了一些关于组合规则清单和自然语言表达能力的最基本问题。因此，许多人致力于发展理论来解释量词的形式属性。相比之下，关于量词意义如何在真实的时间中被处理的工作相对较少，特别是它们的真值条件导入如何被大脑的非语言系统使用，例如在验证任务中。该项目研究了量化表达的真实的时间处理，使用一种新的实验范式，称为自步速计数，它允许研究人员收集细粒度的时间信息，关于受试者如何收集信息增量验证任务，涉及计数或幅度估计。这种时间信息可以揭示由定量表达式触发的验证策略之间的细微差异。特别是，验证配置文件触发的语义等价的定量限定词，具有不同的形态句法结构，可以被证明是不同的系统。这些发现为量化理论提供了动力，该理论将复杂的量词分解为比标准公认的更小的构建块。

Quantificational expressions such as EVERY, SOME, MOST, MORE THAN HALF, etc. play a central role in the scientific study of language because they introduce some of the most fundamental questions about the inventory of combinatorial rules and the expressive power found in natural languages. Consequently, much effort has been devoted to developing theories that explain the formal properties of quantifiers. In contrast, there is relatively little work on how quantifier meanings are processed in real time, specifically how their truth conditional import is used by non-linguistic systems of the mind, for instance in verification tasks. This project investigates real time processing of quantified expressions using a novel experimental paradigm called Self-Paced Counting, which allows researchers to gather fine-grained timing information about how subjects gather information incrementally in verification tasks that involve counting or magnitude estimation. This timing information can reveal subtle differences between verification strategies triggered by quantificational expressions. In particular, verification profiles triggered by semantically equivalent quantificational determiners that have different morphosyntactic structure can be shown to differ systematically. Such findings provide motivation for a theory of quantification that decomposes complex quantifiers into smaller building blocks than is standardly recognized.