Naslov
Multilingual Comparative Analysis of Deep-Learning Dependency Parsing Results Using Parallel Corpora

Autori
Alves, Diego ; Bekavac, Božo ; Tadić, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the LREC 2022 15th Workshop on Building and Using Comparable Corpora (BUCC 2022) / Rapp, Reinhard ; Zweigenbaum, Pierre ; Sharoff, Serge - Marseille : European Language Resources Association (ELRA), 2022, 33-42

ISBN
979-10-95546-94-8

Skup
15th Workshop on Building and Using Comparable Corpora (BUCC 2022)

Mjesto i datum
Marseille, Francuska, 25.06.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
dependency parsing ; typology ; multilingualism

Sažetak
This article presents a comparative analysis of dependency parsing results for a set of 16 languages, coming from a large variety of linguistic families and genera, whose parallel corpora were used to train a deep-learning tool. Results are analyzed in comparison to an innovative way of classifying languages concerning the head directionality parameter used to perform a quantitative syntactic typological classification of languages. It has been shown that, despite using parallel corpora, there is a large discrepancy in terms of LAS results. The obtained results show that this heterogeneity is mainly due to differences in the syntactic structure of the selected languages, where Indo- European ones, especially Romance languages, have the best scores. It has been observed that the differences in the size of the representation of each language in the language model used by the deep-learning tool also play a major role in the dependency parsing efficacy. Other factors, such as the number of dependency parsing labels may also have an influence on results with more complex labeling systems such as the Polish language.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti, Filologija

POVEZANOST RADA