This paper introduces CogNet, a new, large-scale lexical database that provides cognates—words of common origin and meaning—across languages. The database currently contains 3.1 million cognate pairs across 338 languages using 35 writing sys- tems. The paper also describes the automated method by which cognates were computed from publicly available wordnets, with an accuracy evaluated to 94%. Finally, statistics and early insights about the cognate data are presented, hinting at a possible future exploitation of the resource1 by various fields of lingustics.

CogNet: a Large-Scale Cognate Database / Batsuren, Khuyagbaatar; Bella, Gabor; Giunchiglia, Fausto. - (2019), pp. 3136-3145. (Intervento presentato al convegno ACL 2019 tenutosi a Firenze nel 28th July-2nd August 2019) [10.18653/v1/P19-1302].

CogNet: a Large-Scale Cognate Database

Batsuren, Khuyagbaatar;Bella, Gabor;Giunchiglia, Fausto
2019-01-01

Abstract

This paper introduces CogNet, a new, large-scale lexical database that provides cognates—words of common origin and meaning—across languages. The database currently contains 3.1 million cognate pairs across 338 languages using 35 writing sys- tems. The paper also describes the automated method by which cognates were computed from publicly available wordnets, with an accuracy evaluated to 94%. Finally, statistics and early insights about the cognate data are presented, hinting at a possible future exploitation of the resource1 by various fields of lingustics.
2019
ACL 2019 The 57th Annual Meeting of the Association for Computational Linguistics: Proceedings of the Conference
Stroudsburg, PA
Association for Computational Linguistics
978-1-950737-48-2
Batsuren, Khuyagbaatar; Bella, Gabor; Giunchiglia, Fausto
CogNet: a Large-Scale Cognate Database / Batsuren, Khuyagbaatar; Bella, Gabor; Giunchiglia, Fausto. - (2019), pp. 3136-3145. (Intervento presentato al convegno ACL 2019 tenutosi a Firenze nel 28th July-2nd August 2019) [10.18653/v1/P19-1302].
File in questo prodotto:
File Dimensione Formato  
2019-ACL-Cognet.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.73 MB
Formato Adobe PDF
2.73 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/244265
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 21
  • ???jsp.display-item.citation.isi??? 10
social impact