From Tokens to Trees: Mapping Syntactic Structures in the Deserts of Data-Scarce Languages
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ADHBWQ4BH" target="_blank" >RIV/00216208:11320/25:DHBWQ4BH - isvavai.cz</a>
Výsledek na webu
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200147491&partnerID=40&md5=1e9caf4ce37c2a2bc79f0a43a5467d98" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200147491&partnerID=40&md5=1e9caf4ce37c2a2bc79f0a43a5467d98</a>
DOI - Digital Object Identifier
—
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
From Tokens to Trees: Mapping Syntactic Structures in the Deserts of Data-Scarce Languages
Popis výsledku v původním jazyce
Low-resource learning in natural language processing focuses on developing effective resources, tools, and technologies for languages that are less popular within the industry and academia. This effort is crucial for several reasons, including ensuring that as many languages as possible are represented digitally, and enhancing access to language technologies for native speakers of minority languages. In this context, this paper outlines the motivation, research lines, and results from a Leonardo Grant - by FBBVA - on low-resource languages and parsing as sequence labeling. The project’s primary aim was to devise fast and accurate methods for low-resource syntactic parsing and to examine evaluation strategies as well as strengths and weaknesses in comparison to alternative parsing strategies. © 2024 Copyright for this paper by its authors.
Název v anglickém jazyce
From Tokens to Trees: Mapping Syntactic Structures in the Deserts of Data-Scarce Languages
Popis výsledku anglicky
Low-resource learning in natural language processing focuses on developing effective resources, tools, and technologies for languages that are less popular within the industry and academia. This effort is crucial for several reasons, including ensuring that as many languages as possible are represented digitally, and enhancing access to language technologies for native speakers of minority languages. In this context, this paper outlines the motivation, research lines, and results from a Leonardo Grant - by FBBVA - on low-resource languages and parsing as sequence labeling. The project’s primary aim was to devise fast and accurate methods for low-resource syntactic parsing and to examine evaluation strategies as well as strengths and weaknesses in comparison to alternative parsing strategies. © 2024 Copyright for this paper by its authors.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
—
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
CEUR Workshop Proc.
ISBN
—
ISSN
1613-0073
e-ISSN
—
Počet stran výsledku
6
Strana od-do
30-35
Název nakladatele
CEUR-WS
Místo vydání
—
Místo konání akce
A Coruna
Datum konání akce
1. 1. 2025
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—