A Web Corpus Analysis of the Italian Grazie Di/Per Alternation

The prepositional variation of grazie di/per + complement ‘thanks for X’ is often acknowledged in Italian grammars but has not yet been adequately examined. I appeal to key tenets of Construction Grammar to analyze 3000 tokens of this construction from the Italian Web 2020 Corpus. To fully probe the conditioning of di/per selection, I pair logistic regression of the entire dataset with a descriptive statistical analysis of various levels of constructional schematicity and frequent individual complements. Results confirm previous descriptions that per is now the majority variant and reveal that significant predictors of preposition selection include complement type (nominal, simple infinitive, compound infinitive), as well as complement complexity and quantity of intervening material (both measured in number of words). However, strong lexico-constructional effects are also observed, such that the older variant di remains strongly preferred in specific micro-constructions (e.g., grazie di tutto ‘thanks for everything’, grazie di esistere ‘thanks for existing’). These findings evince a complex case of variation which requires the joint consideration of both overall patterns and fine-grained constructional distinctions.

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Publication Details

Journal
Languages
Published
2025-09-19
DOI
https://doi.org/10.3390/languages10090241
Primary Topic
Linguistic Studies and Language Acquisition
Type
article
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article

A Web Corpus Analysis of the Italian Grazie Di/Per Alternation

Mark Hoff
Languages
Linguistic Studies and Language Acquisition
article

A Web Corpus Analysis of the Italian Grazie Di/Per Alternation

Mark Hoff
article en

Abstract

The prepositional variation of grazie di/per + complement ‘thanks for X’ is often acknowledged in Italian grammars but has not yet been adequately examined. I appeal to key tenets of Construction Grammar to analyze 3000 tokens of this construction from the Italian Web 2020 Corpus. To fully probe the conditioning of di/per selection, I pair logistic regression of the entire dataset with a descriptive statistical analysis of various levels of constructional schematicity and frequent individual complements. Results confirm previous descriptions that per is now the majority variant and reveal that significant predictors of preposition selection include complement type (nominal, simple infinitive, compound infinitive), as well as complement complexity and quantity of intervening material (both measured in number of words). However, strong lexico-constructional effects are also observed, such that the older variant di remains strongly preferred in specific micro-constructions (e.g., grazie di tutto ‘thanks for everything’, grazie di esistere ‘thanks for existing’). These findings evince a complex case of variation which requires the joint consideration of both overall patterns and fine-grained constructional distinctions.

LanguagesVol. 10(9)
Queens College, CUNY (US)
Openalex Percentile: Top 87%
Linguistic Studies and Language Acquisition
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