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

Matteo Pellegrini, Alessandra Teresa Cignarella

Risultato della ricerca: Contributo in libroContributo a convegno

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteCEUR Workshop Proceedings
Pagine1-6
Numero di pagine6
Stato di pubblicazionePubblicato - 2020
Evento7th Italian Conference on Computational Linguistics, CLiC-it 2020 - Bologna
Durata: 1 mar 20213 mar 2021

Serie di pubblicazioni

NomeCEUR WORKSHOP PROCEEDINGS

Convegno

Convegno7th Italian Conference on Computational Linguistics, CLiC-it 2020
CittàBologna
Periodo1/3/213/3/21

Keywords

  • Entropy
  • Lexicon
  • Morphology
  • Predictability

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