Zero-shot Cross-lingual POS Tagging for Filipino

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A7IVJPSUV" target="_blank" >RIV/00216208:11320/25:7IVJPSUV - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204281744&partnerID=40&md5=dce287ff65885c38d67ee1019c2837dc" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204281744&partnerID=40&md5=dce287ff65885c38d67ee1019c2837dc</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Zero-shot Cross-lingual POS Tagging for Filipino

Original language description

Supervised learning approaches in NLP, exemplified by POS tagging, rely heavily on the presence of large amounts of annotated data. However, acquiring such data often requires significant amount of resources and incurs high costs. In this work, we explore zero-shot cross-lingual transfer learning to address data scarcity issues in Filipino POS tagging, particularly focusing on optimizing source language selection. Our zero-shot approach demonstrates superior performance compared to previous studies, with top-performing fine-tuned PLMs achieving F1 scores as high as 79.10%. The analysis reveals moderate correlations between cross-lingual transfer performance and specific linguistic distances–featural, inventory, and syntactic–suggesting that source languages with these features closer to Filipino provide better results. We identify tokenizer optimization as a key challenge, as PLM tokenization sometimes fails to align with meaningful representations, thus hindering POS tagging performance. ©2024 Association for Computational Linguistics.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

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Continuities

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Publication year

2024

Confidentiality

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

Article name in the collection

FieldMatters - Workshop NLP Appl. Field Linguist. - Proc. Workshop

ISBN

979-889176158-2

ISSN

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e-ISSN

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Number of pages

9

Pages from-to

69-77

Publisher name

Association for Computational Linguistics (ACL)

Place of publication

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Event location

Bangkok

Event date

Jan 1, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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