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Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs

The combining of individual concepts to form an emergent concept is a fundamental aspect of language, yet much less is known about it than about processing isolated words or sentences. To facilitate research on conceptual combination, we provide meaningfulness ratings for a large set of (2,160) noun...

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Autores principales: Graves, William W., Binder, Jeffrey R., Seidenberg, Mark S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663253/
https://www.ncbi.nlm.nih.gov/pubmed/23055162
http://dx.doi.org/10.3758/s13428-012-0256-3
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author Graves, William W.
Binder, Jeffrey R.
Seidenberg, Mark S.
author_facet Graves, William W.
Binder, Jeffrey R.
Seidenberg, Mark S.
author_sort Graves, William W.
collection PubMed
description The combining of individual concepts to form an emergent concept is a fundamental aspect of language, yet much less is known about it than about processing isolated words or sentences. To facilitate research on conceptual combination, we provide meaningfulness ratings for a large set of (2,160) noun–noun pairs. Half of these pairs (1,080) are reversed versions of the other half (e.g., ski jacket and jacket ski), to facilitate the comparison of successful and unsuccessful conceptual combination independently of constituent lexical items. The computer code used for obtaining these ratings through a Web interface is provided. To further enhance the usefulness of this resource, ancillary measures obtained from other sources are also provided for each pair. These measures include associate production norms, contextual relatedness in terms of latent semantic analysis distance, total number of letters, phrase-level usage frequency, and word-level usage frequency summed across the words in each pair. Results of correlation and regression analyses are also provided for a quantitative description of the stimulus set. A subset of these stimuli was used to identify neural correlates of successful conceptual combination Graves, Binder, Desai, Conant, & Seidenberg, (NeuroImage 53:638–646, 2010). The stimuli can be used in other research and also provide benchmark data for evaluating the effectiveness of computational algorithms for predicting meaningfulness of noun–noun pairs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.3758/s13428-012-0256-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-36632532013-05-24 Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs Graves, William W. Binder, Jeffrey R. Seidenberg, Mark S. Behav Res Methods Article The combining of individual concepts to form an emergent concept is a fundamental aspect of language, yet much less is known about it than about processing isolated words or sentences. To facilitate research on conceptual combination, we provide meaningfulness ratings for a large set of (2,160) noun–noun pairs. Half of these pairs (1,080) are reversed versions of the other half (e.g., ski jacket and jacket ski), to facilitate the comparison of successful and unsuccessful conceptual combination independently of constituent lexical items. The computer code used for obtaining these ratings through a Web interface is provided. To further enhance the usefulness of this resource, ancillary measures obtained from other sources are also provided for each pair. These measures include associate production norms, contextual relatedness in terms of latent semantic analysis distance, total number of letters, phrase-level usage frequency, and word-level usage frequency summed across the words in each pair. Results of correlation and regression analyses are also provided for a quantitative description of the stimulus set. A subset of these stimuli was used to identify neural correlates of successful conceptual combination Graves, Binder, Desai, Conant, & Seidenberg, (NeuroImage 53:638–646, 2010). The stimuli can be used in other research and also provide benchmark data for evaluating the effectiveness of computational algorithms for predicting meaningfulness of noun–noun pairs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.3758/s13428-012-0256-3) contains supplementary material, which is available to authorized users. Springer-Verlag 2012-10-06 2013 /pmc/articles/PMC3663253/ /pubmed/23055162 http://dx.doi.org/10.3758/s13428-012-0256-3 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Graves, William W.
Binder, Jeffrey R.
Seidenberg, Mark S.
Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title_full Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title_fullStr Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title_full_unstemmed Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title_short Noun–noun combination: Meaningfulness ratings and lexical statistics for 2,160 word pairs
title_sort noun–noun combination: meaningfulness ratings and lexical statistics for 2,160 word pairs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663253/
https://www.ncbi.nlm.nih.gov/pubmed/23055162
http://dx.doi.org/10.3758/s13428-012-0256-3
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