The Role of Typological Feature Prediction in NLP and Linguistics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AB8UQ435M" target="_blank" >RIV/00216208:11320/25:B8UQ435M - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185579052&doi=10.1162%2fcoli_a_00498&partnerID=40&md5=7affcc9be399d4088d80d38e7c519479" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185579052&doi=10.1162%2fcoli_a_00498&partnerID=40&md5=7affcc9be399d4088d80d38e7c519479</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1162/coli_a_00498" target="_blank" >10.1162/coli_a_00498</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Role of Typological Feature Prediction in NLP and Linguistics

Popis výsledku v původním jazyce

Computational typology has gained traction in the field of Natural Language Processing (NLP) in recent years, as evidenced by the increasing number of papers on the topic and the establishment of a Special Interest Group on the topic (SIGTYP), including the organization of successful workshops and shared tasks. A considerable amount of work in this sub-field is concerned with prediction of typological features, for example, for databases such as the World Atlas of Language Structures (WALS) or Grambank. Prediction is argued to be useful either because (1) it allows for obtaining feature values for relatively undocumented languages, alleviating the sparseness in WALS, in turn argued to be useful for both NLP and linguistics; and (2) it allows us to probe models to see whether or not these typological features are encapsulated in, for example, language representations. In this article, we present a critical stance concerning prediction of typological features, investigating to what extent this line of research is aligned with purported needs—both from the perspective of NLP practitioners, and perhaps more importantly, from the perspective of linguists specialized in typology and language documentation. We provide evidence that this line of research in its current state suffers from a lack of interdisciplinary alignment. Based on an extensive survey of the linguistic typology community, we present concrete recommendations for future research in order to improve this alignment between linguists and NLP researchers, beyond the scope of typological feature prediction. © 2024 Association for Computational Linguistics.

Název v anglickém jazyce

The Role of Typological Feature Prediction in NLP and Linguistics

Popis výsledku anglicky

Computational typology has gained traction in the field of Natural Language Processing (NLP) in recent years, as evidenced by the increasing number of papers on the topic and the establishment of a Special Interest Group on the topic (SIGTYP), including the organization of successful workshops and shared tasks. A considerable amount of work in this sub-field is concerned with prediction of typological features, for example, for databases such as the World Atlas of Language Structures (WALS) or Grambank. Prediction is argued to be useful either because (1) it allows for obtaining feature values for relatively undocumented languages, alleviating the sparseness in WALS, in turn argued to be useful for both NLP and linguistics; and (2) it allows us to probe models to see whether or not these typological features are encapsulated in, for example, language representations. In this article, we present a critical stance concerning prediction of typological features, investigating to what extent this line of research is aligned with purported needs—both from the perspective of NLP practitioners, and perhaps more importantly, from the perspective of linguists specialized in typology and language documentation. We provide evidence that this line of research in its current state suffers from a lack of interdisciplinary alignment. Based on an extensive survey of the linguistic typology community, we present concrete recommendations for future research in order to improve this alignment between linguists and NLP researchers, beyond the scope of typological feature prediction. © 2024 Association for Computational Linguistics.

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

Computational Linguistics

ISSN

0891-2017

e-ISSN

—

Svazek periodika

50

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

781-794

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85185579052