Interaction of Information Content and Frequency as Predictors of Verbs’ Lengths

  • Michael RichterEmail author
  • Yuki Kyogoku
  • Max Kölbl
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)


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.


Information Content Frequency Linear mixed models Economy in interactions Aspect 



This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project number: 357550571.


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Authors and Affiliations

  1. 1.Natural Language Processing GroupUniversität LeipzigLeipzigGermany

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