Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A8CDNPPHI" target="_blank" >RIV/00216208:11320/23:8CDNPPHI - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174836652&partnerID=40&md5=dde09065d6e1cc3cf207198aade9f20f" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174836652&partnerID=40&md5=dde09065d6e1cc3cf207198aade9f20f</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language

Popis výsledku v původním jazyce

"In this paper we address the scarcity of annotated data for NArabizi, a Romanized form of North African Arabic used mostly on social media, which poses challenges for Natural Language Processing (NLP). We introduce an enriched version of NArabizi Treebank (Seddah et al., 2020) with three main contributions: the addition of two novel annotation layers (named entity recognition and offensive language detection) and a re-annotation of the tokenization, morpho-syntactic and syntactic layers that ensure annotation consistency. Our experimental results, using different tokenization schemes, showcase the value of our contributions and highlight the impact of working with non-gold tokenization for NER and dependency parsing. To facilitate future research, we make these annotations publicly available. Our enhanced NArabizi Treebank paves the way for creating sophisticated language models and NLP tools for this under-represented language. © 2023 Association for Computational Linguistics."

Název v anglickém jazyce

Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting an Under-Resourced Language

Popis výsledku anglicky

"In this paper we address the scarcity of annotated data for NArabizi, a Romanized form of North African Arabic used mostly on social media, which poses challenges for Natural Language Processing (NLP). We introduce an enriched version of NArabizi Treebank (Seddah et al., 2020) with three main contributions: the addition of two novel annotation layers (named entity recognition and offensive language detection) and a re-annotation of the tokenization, morpho-syntactic and syntactic layers that ensure annotation consistency. Our experimental results, using different tokenization schemes, showcase the value of our contributions and highlight the impact of working with non-gold tokenization for NER and dependency parsing. To facilitate future research, we make these annotations publicly available. Our enhanced NArabizi Treebank paves the way for creating sophisticated language models and NLP tools for this under-represented language. © 2023 Association for Computational Linguistics."

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)

Projekt

—

Návaznosti

—

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

"Proc. Annu. Meet. Assoc. Comput Linguist."

ISBN

978-195942983-8

ISSN

0736-587X

e-ISSN

—

Počet stran výsledku

13

Strana od-do

266-278

Název nakladatele

Association for Computational Linguistics (ACL)

Místo vydání

—

Místo konání akce

Cham

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—