Managing Noise in Part-of-Speech Tagging for Extremely Low-Resource Languages: Comparing Strategies for Corpus Collection and Annotation in Dagur and Alsatian

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3ASRCF7U3B" target="_blank" >RIV/00216208:11320/26:SRCF7U3B - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.openedition.org/corpus/9177" target="_blank" >https://journals.openedition.org/corpus/9177</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.4000/13654" target="_blank" >10.4000/13654</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Managing Noise in Part-of-Speech Tagging for Extremely Low-Resource Languages: Comparing Strategies for Corpus Collection and Annotation in Dagur and Alsatian

Popis výsledku v původním jazyce

Although Dagur and Alsatian represent two typologically distant language families, they share several similarities: both languages are endangered, do not have a unified spelling system, and have few available digital corpora. Given these challenges, the main aim of this article is to compare the noise in corpora for these languages and its impact on part-of-speech (POS) annotation and tagging. We first discuss what strategies can be used to reduce the noise due to spelling inconsistencies observed during corpus collection, using Dagur as an example. We then observe that the distributions of POS trigrams in the manually annotated Dagur and Alsatian corpora are similar to those of typologically related languages in UD v2.12, laying the foundations for experimenting with zero-shot transfer approaches for automatic POS tagging. We evaluate some simple noise reduction strategies for POS tagging using the example of the Alsatian dialects and relying on their proximity to standard German. The results obtained confirm the important role of linguistic proximity in automatic POS tagging and the effectiveness of the proposed data transformation method. However, they also invite further interpretation of the capacities of multilingual models.

Název v anglickém jazyce

Managing Noise in Part-of-Speech Tagging for Extremely Low-Resource Languages: Comparing Strategies for Corpus Collection and Annotation in Dagur and Alsatian

Popis výsledku anglicky

Although Dagur and Alsatian represent two typologically distant language families, they share several similarities: both languages are endangered, do not have a unified spelling system, and have few available digital corpora. Given these challenges, the main aim of this article is to compare the noise in corpora for these languages and its impact on part-of-speech (POS) annotation and tagging. We first discuss what strategies can be used to reduce the noise due to spelling inconsistencies observed during corpus collection, using Dagur as an example. We then observe that the distributions of POS trigrams in the manually annotated Dagur and Alsatian corpora are similar to those of typologically related languages in UD v2.12, laying the foundations for experimenting with zero-shot transfer approaches for automatic POS tagging. We evaluate some simple noise reduction strategies for POS tagging using the example of the Alsatian dialects and relying on their proximity to standard German. The results obtained confirm the important role of linguistic proximity in automatic POS tagging and the effectiveness of the proposed data transformation method. However, they also invite further interpretation of the capacities of multilingual models.

Druh

J_ost - Ostatní články v recenzovaných periodicích

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

2025

Kód důvěrnosti údajů

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

Název periodika

Corpus

ISSN

1765-3126

e-ISSN

—

Svazek periodika

2025

Číslo periodika v rámci svazku

26

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

19

Strana od-do

1-19

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—