Comparison of various approaches to tagging for the inflectional Slovak language

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AQU27UJUV" target="_blank" >RIV/00216208:11320/25:QU27UJUV - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216275:25410/24:39922254

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196088719&doi=10.7717%2fPEERJ-CS.2026&partnerID=40&md5=d86c5ff910c37031dd275ab7f425af41" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196088719&doi=10.7717%2fPEERJ-CS.2026&partnerID=40&md5=d86c5ff910c37031dd275ab7f425af41</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7717/PEERJ-CS.2026" target="_blank" >10.7717/PEERJ-CS.2026</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of various approaches to tagging for the inflectional Slovak language

Popis výsledku v původním jazyce

Morphological tagging provides essential insights into grammar, structure, and the mutual relationships of words within the sentence. Tagging text in a highly inflectional language presents a challenging task due to word ambiguity. This research aims to compare six different automatic taggers for the inflectional Slovak language, seeking for the most accurate tagger for literary and non-literary texts. Our results indicate that it is useful to differentiate texts into literary and non-literary and subsequently, based on the text style to deploy a tagger. For literary texts, UDPipe2 outperformed others in seven out of nine examined tagset positions. Conversely, for non-literary texts, the RNNTagger exhibited the highest performance in eight out of nine examined tagset positions. The RNNTagger is recommended for both types of the text, the best captures the inflection of the Slovak language, but UDPipe2 demonstrates a higher accuracy for literary texts. Despite dataset size limitations, this study emphasizes the suitability of various taggers for the inflectional languages like Slovak. © Copyright 2024 Benko et al.

Název v anglickém jazyce

Comparison of various approaches to tagging for the inflectional Slovak language

Popis výsledku anglicky

Morphological tagging provides essential insights into grammar, structure, and the mutual relationships of words within the sentence. Tagging text in a highly inflectional language presents a challenging task due to word ambiguity. This research aims to compare six different automatic taggers for the inflectional Slovak language, seeking for the most accurate tagger for literary and non-literary texts. Our results indicate that it is useful to differentiate texts into literary and non-literary and subsequently, based on the text style to deploy a tagger. For literary texts, UDPipe2 outperformed others in seven out of nine examined tagset positions. Conversely, for non-literary texts, the RNNTagger exhibited the highest performance in eight out of nine examined tagset positions. The RNNTagger is recommended for both types of the text, the best captures the inflection of the Slovak language, but UDPipe2 demonstrates a higher accuracy for literary texts. Despite dataset size limitations, this study emphasizes the suitability of various taggers for the inflectional languages like Slovak. © Copyright 2024 Benko et al.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PeerJ Computer Science

ISSN

2376-5992

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

2024

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

31

Strana od-do

1-31

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85196088719