Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90393
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dc.contributorDepartment of Computingen_US
dc.contributorDepartment of Chinese and Bilingual Studiesen_US
dc.creatorXiang, Ren_US
dc.creatorChersoni, Een_US
dc.creatorIacoponi, Len_US
dc.creatorSantus, Een_US
dc.date.accessioned2021-06-28T07:25:49Z-
dc.date.available2021-06-28T07:25:49Z-
dc.identifier.urihttp://hdl.handle.net/10397/90393-
dc.language.isoenen_US
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 International Licence. Licence details: http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Xiang, R., Chersoni, E., Iacoponi, L., & Santus, E. (2020, December). The CogALex Shared Task on Monolingual and Multilingual Identification of Semantic Relations. In Proceedings of the Workshop on the Cognitive Aspects of the Lexicon (pp. 46-53) is available at https://www.aclweb.org/anthology/2020.cogalex-1.5/en_US
dc.titleThe CogALex shared task on monolingual and multilingual identification of semantic relationsen_US
dc.typeConference Paperen_US
dc.identifier.spage46en_US
dc.identifier.epage53en_US
dcterms.abstractThe shared task of the CogALex-VI workshop focuses on the monolingual and multilingual identification of semantic relations. We provided training and validation data for the following languages: English, German and Chinese. Given a word pair, systems had to be trained to identify which relation holds between them, with possible choices being synonymy, antonymy, hypernymy and no relation at all.en_US
dcterms.abstractTwo test sets were released for evaluating the participating systems. One containing pairs for each of the training languages (systems were evaluated in a monolingual fashion) and the other one proposing a surprise language to test the crosslingual transfer capabilities of the systems.en_US
dcterms.abstractAmong the submitted systems, top performance was achieved by a transformer-based model in both the monolingual and in the multilingual setting, for all the tested languages, proving the potentials of this recently-introduced neural architecture.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the Workshop on Cognitive Aspects of the Lexicon, December 2020, p. 46-53en_US
dcterms.issued2020-
dc.relation.ispartofbookProceedings of the Workshop on the Cognitive Aspects of the Lexiconen_US
dc.description.validate202106 bcvcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera0670-n27-
dc.description.pubStatusPublisheden_US
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