SemR-11: a multi-lingual gold-standard for semantic similarity and relatedness for eleven languages
Barzegar, Siamak Davis, Brian Zarrouk, Manel Handschuh, Siegfried Freitas, André
Barzegar, Siamak
Davis, Brian
Zarrouk, Manel
Handschuh, Siegfried
Freitas, André
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Publication Date
2018-05-07
Type
Conference Paper
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Barzegar, Siamak, Davis, Brian, Zarrouk, Manel, Handschuh, Siegfried, & Freitas, André. (2018). SemR-11: a multi-lingual gold-standard for semantic similarity and relatedness for eleven languages. Paper presented at the 11th edition of the Language Resources and Evaluation Conference (LREC2018), Miyazaki, Japan, 7-12 May.
Abstract
This work describes SemR-11, a multi-lingual dataset for evaluating semantic similarity and relatedness for 11 languages (German, French, Russian, Italian, Dutch, Chinese, Portuguese, Swedish, Spanish, Arabic and Persian). Semantic similarity and relatedness gold standards have been initially used to support the evaluation of semantic distance measures in the context of linguistic and knowledge resources and distributional semantic models. SemR-11 builds upon the English gold-standards of Miller & Charles (MC), Rubenstein & Goodenough (RG), WordSimilarity 353 (WS-353), and Simlex-999, providing a canonical translation for them. The final dataset consists of 15,917 word pairs and can be used to support the construction and evaluation of semantic similarity/relatedness and distributional semantic models. As a case study, the SemR-11 test collections was used to investigate how different distributional semantic models built from corpora in different languages and with different sizes perform in computing semantic relatedness similarity and relatedness tasks.
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European Language Resources Association
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Attribution-NonCommercial-NoDerivs 3.0 Ireland