Inferring inflection classes with description length

• Autorzy: Beniamine S. , Bonami O. , Sagot B.

Identyfikatory

DOI

10.15398/jlm.v5i3.184

• Języki publikacji: EN

Abstrakty

EN

We discuss the notion of an inflection class system, a traditional ingredient of the description of inflection systems of nontrivial complexity. We distinguish systems of microclasses, which partition a set of lexemes in classes with identical behavior, and systems of macroclasses, which group lexemes that are similar enough in a few larger classes. On the basis of the intuition that macroclasses should contribute to a concise description of the system, we propose one algorithmic method for inferring macroclasses from raw inflectional paradigms, based on minimisation of the description length of the system under a given strategy of identifying morphological alternations in paradigms. We then exhibit classifications produced by our implementation on French and European Portuguese conjugation data and argue that they constitute an appropriate systematisation of traditional classifications. To arrive at such a convincing systematisation, it was crucial for us to use a local approach to inflection class similarity (based on pairwise comparisons of paradigm cells) rather than a global approach (based on the simultaneous comparison of all cells). We conclude that it is indeed possible to infer inflectional macroclasses objectively.

Słowa kluczowe

EN

morphology; MDL; Minimum Description Length; inflection classes

• Wydawca: Instytut Podstaw Informatyki PAN
• Czasopismo: Journal of Language Modelling
• Rocznik: 2017
• Tom: Vol. 5, No. 3
• Strony: 465--525
• Opis fizyczny: Bibliogr. 62 poz., rys., tab., wykr.

Twórcy

autor

Beniamine S.

• Université Paris Diderot, Laboratoire de linguistique formelle, France

autor

Bonami O.

• Université Paris Diderot, Laboratoire de linguistique formelle, France

autor

Sagot B.

• Inria, France

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).