Interactive property attribution in concept combination
Interactive property attribution in concept combination
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DOI：
10.3758/bf03211572
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发表时间：
2000-01-01
影响因子：
2.4
通讯作者：
Glucksberg, S
中科院分区：
文献类型：
--
作者：
Estes, Z;Glucksberg, S
我们解决的问题是人们如何理解名词-名词属性复合词。比对和比较模型表明，组成概念的相似性指导解释。作为替代方案，我们提出了一种交互式属性归属模型，其中修饰符和头部概念具有不同的功能：头部提供相关维度，而修饰符提供归属的候选特征。根据我们的模型，尺寸和功能的相互作用，而不是成分的相似性，指导解释。在这项研究中，我们实证对比了这两个模型，保持成分相似性的化合物不变，而变化的修饰语特征显着性和头部尺寸相关性的相互作用。由中心概念和与之相关的属性维度以及在该维度上具有显著属性的修饰语组成的复合词，通过属性归属的方法得到解释。其他成分相似性相当但缺乏显著性-关联交互作用的复合词则不被归因。交互属性归因模型能更准确地预测名词-名词复合词的解释。
We address the question of how people understand attributive noun-noun compounds. Alignment-and-comparison models suggest that the similarity of the constituent concepts guides interpretation. We propose, as an alternative, an interactive property attribution model wherein the modifier and head concepts have different functions: The head provides relevant dimensions, whereas the modifier provides candidate features for attribution. According to our model, the interaction of dimensions and features, rather than constituent similarity, guides interpretation. In this study, we empirically contrasted the two models by holding constituent similarity of compounds constant while varying the interaction of modifier feature salience and head dimension relevance. Compounds consisting of a head concept with a relevant dimension for attribution and a modifier with a salient property on that dimension were interpreted by means of property attribution. Other compounds with equivalent constituent similarity, but lacking the high salience-relevance interaction, were not interpreted by means of attribution. The interactive property attribution model more accurately predicted interpretation of noun-noun compounds.