The Role of Contrast Categories in Natural Language Concepts

Verbeemen, Timothy; Vanoverberghe, Veerle; Storms, Gerrit; Ruts, Wim

doi:10.1006/jmla.2000.2748

Cited by 18 publications

(40 citation statements)

References 33 publications

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“…Because of the large effort involved in collecting and analyzing exemplar and feature norms, we used existing normative data for all natural kind and for one artifact concept (vehicles ). These data were used in Storms et al (2000) and in Verbeemen et al (2001). For the remaining nine artifact concepts, new data were collected using identical procedures.…”

Section: Methodsmentioning

confidence: 99%

“…To investigate the linear separability of category boundaries, these eight concepts were combined into the following eight semantically related contrast pairs: insects-fish, insects-birds, insects-mammals, fish-birds, fish-mammals, birds-mammals, trees-flowers, and fruits-vegetables . For the matrix-filling task, all exemplars generated in the generation studies from Storms et al (2000) and from Verbeemen et al (2001) were selected. Furthermore, all features that were generated by at least 2 (out of 10) participants from the feature generation studies described in the same articles were selected.…”

Section: Methodsmentioning

confidence: 99%

“…To address the problem of finding the appropriate similarity space in which to test for linear separability, we adopt a different approach from that of Malt et al We compute proximities between category items on the basis of a large set of characteristic features of the categories themselves, based on a generation task. This approach has been successfully used before in several studies (e.g., Hampton, 1979;Storms, De Boeck, & Ruts, 2000;Storms, De Boeck, Van Mechelen, & Ruts, 1996;Verbeemen, Vanoverberghe, Storms, & Ruts, 2001) to predict a number of category-related measures. Three major tasks are used to gather the necessary data.…”

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Linear separability in superordinate natural language concepts

2004

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Two experiments are reported in which linear separability was investigatedin superordinate natural language concept pairs (e.g., toiletry-sewing gear). Representations of the exemplars of semantically related concept pairs were derived in two to five dimensions using multidimensional scaling (MDS) of similarities based on possession of the concept features. Next, category membership, obtained from an exemplar generation study (in Experiment 1) and from a forced-choice classification task (in Experiment 2) was predicted from the coordinates of the MDS representation using log linear analysis. The results showed that all natural kind concept pairs were perfectly linearly separable, whereas artifact concept pairs showed several violations. Clear linear separability of natural language concept pairs is in line with independent cue models. The violations in the artifact pairs, however, yield clear evidence against the independent cue models.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Linear separability in superordinate natural language concepts

2004

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“…The shorter the path between two nodes, the more similar they are considered to be (Sattath & Tversky, 1977). The advantage of using cluster analysis is that it yields a more reliable estimate of the closest pair, since the clustering results are determined by all pairwise similarities together, rather than just the pairwise similarity with the maximal value (Verbeemen et al, 2001). …”

Section: Corpus Analysismentioning

confidence: 99%

“…The procedure followed a suggestion by Verbeemen, Vanoverberghe, Storms, and Ruts (2001) and comprised the identification of the category (from a given set) that was regarded most similar to the target category. A minimum of similarity between two categories is required for there to be (an effect of) external features.…”

Section: Studymentioning

confidence: 99%

The generalized polymorphous concept account of graded structure in abstract categories

et al. 2011

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categories present with graded structure. The extent to which feature commonality between exemplars and category provides a satisfying account of this graded structure varies from one abstract category to the other (Hampton, 1981). We investigate whether the incorporation of features that exemplars share with external categories yields an improved account of abstract categories' graded structures. In doing so, we follow the suggestion that abstract categories are relational in nature (Goldstone, 1996;Wiemer-Hastings & Xu, 2005). The generalized polymorphous concept model, which incorporates both types of features, is found to improve the account of typicality and category membership in three of seven studied abstract categories. These three categories are found to be the most abstract, suggesting that it is appropriate to think of abstract categories as varying along a continuum of abstractness/interrelatedness rather than as a distinct type of category altogether.

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Features of graded category structure: Generalizing the family resemblance and polymorphous concept models

Dry¹,

Storms²

2010

Acta Psychologica

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The Role of Contrast Categories in Natural Language Concepts

Cited by 18 publications

References 33 publications

Linear separability in superordinate natural language concepts

Linear separability in superordinate natural language concepts

The generalized polymorphous concept account of graded structure in abstract categories

Features of graded category structure: Generalizing the family resemblance and polymorphous concept models

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