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

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.
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].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/244265
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