Despite being one of the most popular tasks in lexical semantics, word similarity has often been limited to the English language. Other languages, even those that are widely spoken such as Spanish, do not have a reliable word similarity evaluation framework. We put forward robust methodologies for the extension of existing English datasets to other languages, both at monolingual and cross-lingual levels. We propose an automatic standardization for the construction of cross-lingual similarity datasets, and provide an evaluation, demonstrating its reliability and robustness. Based on our procedure and taking the RG-65 word similarity dataset as a reference, we release two high-quality Spanish and Farsi (Persian) monolingual datasets, and fifteen cross-lingual datasets for six languages: English, Spanish, French, German, Portuguese, and Farsi.
A framework for the construction of monolingual and cross-lingual Word Similarity Datasets / CAMACHO COLLADOS, Jose'; Pilehvar, MOHAMMED TAHER; Navigli, Roberto. - ELETTRONICO. - 1:(2015), pp. 1-7. (Intervento presentato al convegno ACL tenutosi a Beijing, China nel Luglio, 2015).
A framework for the construction of monolingual and cross-lingual Word Similarity Datasets
CAMACHO COLLADOS, JOSE';PILEHVAR, MOHAMMED TAHER;NAVIGLI, ROBERTO
2015
Abstract
Despite being one of the most popular tasks in lexical semantics, word similarity has often been limited to the English language. Other languages, even those that are widely spoken such as Spanish, do not have a reliable word similarity evaluation framework. We put forward robust methodologies for the extension of existing English datasets to other languages, both at monolingual and cross-lingual levels. We propose an automatic standardization for the construction of cross-lingual similarity datasets, and provide an evaluation, demonstrating its reliability and robustness. Based on our procedure and taking the RG-65 word similarity dataset as a reference, we release two high-quality Spanish and Farsi (Persian) monolingual datasets, and fifteen cross-lingual datasets for six languages: English, Spanish, French, German, Portuguese, and Farsi.File | Dimensione | Formato | |
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