Interaction of Information Content and Frequency as Predictors of Verbs’ Lengths
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10427039" target="_blank" >RIV/00216208:11320/19:10427039 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Interaction of Information Content and Frequency as Predictors of Verbs’ Lengths
Original language description
The topic of this paper is the interaction of Average Information Content (IC) and frequency of aspect-coded verbs in Linear Mixed Effect Models as predictors of the verbs’ lengths. For 30 languages in focus, it came to light that IC and frequency do not have a simultaneous, positive impact on the length of verb forms: the effect of the IC is high, when the effect of frequency is low and vice versa. This is an indication of Uniform Information Density [13, 14, 15, 16]. Additionally, the predictors IC and frequency yield high correlations between predicted and actual verbs’ lengths.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů