(Stem and word) predictability in Italian verb paradigms: An entropy-based study exploiting the new resource Leffi

Matteo Pellegrini, Alessandra Teresa Cignarella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present LeFFI, an inflected lexicon of Italian listing all the available wordforms of 2,053 verbs. We then use this resource to perform an entropy-based analysis of the mutual predictability of wordforms within Italian verb paradigms, and compare our findings to the ones of previous work on stem predictability in Italian verb inflection.
Original languageEnglish
Title of host publicationCEUR Workshop Proceedings
Pages1-6
Number of pages6
Publication statusPublished - 2020
Event7th Italian Conference on Computational Linguistics, CLiC-it 2020 - Bologna
Duration: 1 Mar 20213 Mar 2021

Publication series

NameCEUR WORKSHOP PROCEEDINGS

Conference

Conference7th Italian Conference on Computational Linguistics, CLiC-it 2020
CityBologna
Period1/3/213/3/21

Keywords

  • Entropy
  • Lexicon
  • Morphology
  • Predictability

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