A large and evolving cognate database

被引：11
|
作者：
Batsuren, Khuyagbaatar [1 ]
Bella, Gabor [2 ]
Giunchiglia, Fausto [2 ,3 ]
机构：
[1] Natl Univ Mongolia, Dept Informat & Comp Sci, Ikh Surguuliin Gudamj 1, Ulaanbaatar 14200, Mongolia
[2] Univ Trento, Dept Informat Engn & Comp Sci, Via Sommar 5, I-38123 Trento, Italy
[3] Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China
来源：
LANGUAGE RESOURCES AND EVALUATION | 2022年 / 56卷 / 01期
关键词：
Cognate; Lexical semantics; Lexical database; INFERENCE; WORDNET;
D O I：
10.1007/s10579-021-09544-6
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
We present CogNet, a large-scale, automatically-built database of sense-tagged cognates-words of common origin and meaning across languages. CogNet is continuously evolving: its current version contains over 8 million cognate pairs over 338 languages and 35 writing systems, with new releases already in preparation. The paper presents the algorithm and input resources used for its computation, an evaluation of the result, as well as a quantitative analysis of cognate data leading to novel insights on language diversity. Furthermore, as an example on the use of large-scale cross-lingual knowledge bases for improving the quality of multilingual applications, we present a case study on the use of CogNet for bilingual lexicon induction in the framework of cross-lingual transfer learning.
引用
收藏
页码：165 / 189
页数：25
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