Derivation predicting inflection

A quantitative study of the relation between derivational history and inflectional behavior in Latin

Datos Bibliográficos

ID20381008
AutoresOlivier Bonami (0000-0003-0688-3855, Université de Paris, CNRS, Laboratoire de linguistique formelle), Maura Pellegrini (0000-0003-4378-5824, Università Cattolica del Sacro Cuore)
Año2022
Volumen46
Número4
Páginas753-792
Fecha de publicación2022-10-27
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaStudies in Language (JOURNAL)
Identificadores de la revistaISSN: 0378-4177 • E-ISSN: 1569-9978
EditorialJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/sl.21002.bon
OpenAlexW4207061270
IdiomaEN
Citas recibidas2
Referencias citadas22

In this paper, we investigate the value of derivational information in predicting the inflectional behavior of lexemes. We focus on Latin, for which large-scale data on both inflection and derivation are easily available. We train boosting tree classifiers to predict the inflection class of verbs and nouns with and without different pieces of derivational information. For verbs, we also model inflectional behavior in a word-based fashion, training the same type of classifier to predict wordforms given knowledge of other wordforms of the same lexemes. We find that derivational information is indeed helpful, and document an asymmetry between the beginning and the end of words, in that the final element in a word is highly predictive, while prefixes prove to be uninformative. The results obtained with the word-based methodology also allow for a finer-grained description of the behavior of different pairs of cells

Inflection · Linguistics · Natural language processing · Noun · Part of speech · Prefix · Computer Science · Natural Language Processing Techniques · Philosophy · Syntax, Semantics, Linguistic Variation · Topic Modeling · Artificial Intelligence