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Translation ambiguity but not word class predicts translation performance*

Published online by Cambridge University Press:  13 July 2012

Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, University of Haifa, Israel
Department of Psychology, Center for Language Science, The Pennsylvania State University, USA
Department of Psychology, Carnegie Mellon University, USA
Address for correspondence: Anat Prior, Department of Learning Disabilities, University of Haifa, Mount Carmel, Haifa, Israel,


We investigated the influence of word class and translation ambiguity on cross-linguistic representation and processing. Bilingual speakers of English and Spanish performed translation production and translation recognition tasks on nouns and verbs in both languages. Words either had a single translation or more than one translation. Translation probability, as determined by normative data, was the strongest predictor of translation production and translation recognition, after controlling for psycholinguistic variables. Word class did not explain additional variability in translation performance, raising the possibility that previous findings of differences between nouns and verbs might be attributed to the greater translation ambiguity of verbs relative to nouns. Proficiency in the second language was associated with quicker and more successful production of translations for ambiguous words, and with more accurate recognition of translations for ambiguous words. Working memory capacity was related to the speed of recognizing low probability translations for ambiguous words. These results underscore the importance of considering translation ambiguity in research on bilingual lexical and conceptual knowledge.

Research Article
Copyright © Cambridge University Press 2012

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Anat Prior was supported by post-doctoral NRSA grant F32HD049255 and by EU-FP7 grant IRG-249163. The writing of this article was also supported in part by NIH Grant HD053146 and NSF Grants BCS-0955090 and OISE-0968369 to Judith F. Kroll and by the NSF Pittsburgh Science of Learning Center. The authors thank Mercedes Farrell, Anna Guitchounts, Sofia Murra, Shayna Watson and Huiling Yu for data collection and coding. The authors also gratefully thank Prof. Ana I. Schwartz and members of the PROBAR Lab from the University of Texas, El Paso, for help in recruiting participants. Finally, the authors wish to thank two anonymous reviewers who made helpful comments and suggestions on a previous version of the paper.


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Translation ambiguity but not word class predicts translation performance*
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Translation ambiguity but not word class predicts translation performance*
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