Dative alternation in Italian-to-Dutch translation

Abstract This study investigates the effect of structural priming on dative alternation in Italian-to-Dutch translation. We analyse variation between the double object construction (DOC) and the prepositional object construction (POC) to determine whether the dative structure in the Italian source text influences the Dutch target text, while controlling for key language-internal factors. The methodology is corpus-based and applies a generalized linear mixed-effects model to a richly annotated dataset of translated sentence pairs ( N = 719). Results show that the Italian construction significantly predicts the Dutch target construction, along with several conditioning variables: animacy of the recipient, length difference between theme and recipient, definiteness of the recipient, and the specific verb involved. These findings align with previous corpus-based studies on structural priming in translation ( De Sutter et al ., 2021 , 2023 ), contribute to the Shared Representation Model ( Schaeffer and Carl, 2013 ), and support the relevance of corpus-based approaches in structural priming research in translation.

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Publication Details

Journal
Languages in Contrast
Published
2026-04-13
DOI
https://doi.org/10.1075/lic.00063.ant
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Dative alternation in Italian-to-Dutch translation

Gert De Sutter, Jelena Vranjes, Joke Daems, Francesca Antonioli
Languages in Contrast
Natural Language Processing Techniques
article

Dative alternation in Italian-to-Dutch translation

Gert De Sutter, Jelena Vranjes, Joke Daems, Francesca Antonioli
article en

Abstract

Abstract This study investigates the effect of structural priming on dative alternation in Italian-to-Dutch translation. We analyse variation between the double object construction (DOC) and the prepositional object construction (POC) to determine whether the dative structure in the Italian source text influences the Dutch target text, while controlling for key language-internal factors. The methodology is corpus-based and applies a generalized linear mixed-effects model to a richly annotated dataset of translated sentence pairs ( N = 719). Results show that the Italian construction significantly predicts the Dutch target construction, along with several conditioning variables: animacy of the recipient, length difference between theme and recipient, definiteness of the recipient, and the specific verb involved. These findings align with previous corpus-based studies on structural priming in translation ( De Sutter et al ., 2021 , 2023 ), contribute to the Shared Representation Model ( Schaeffer and Carl, 2013 ), and support the relevance of corpus-based approaches in structural priming research in translation.

Languages in Contrast
Ghent University (BE)
Quality Education
Openalex Percentile: Top 25%
Natural Language Processing Techniques
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