Multilingual enrichment of disease biomedical ontologies

Léo Bouscarrat (1, 2, 3) , Antoine Bonnefoy (3) , Cécile Capponi (1) , Carlos Ramisch (2)

1 QARMA - éQuipe d'AppRentissage de MArseille
2 TALEP - Traitement Automatique du Langage Ecrit et Parlé
3 EURA NOVA

Translating biomedical ontologies is an important challenge, but doing it manually requires much time and money. We study the possibility to use open-source knowledge bases to translate biomedical ontologies. We focus on two aspects: coverage and quality. We look at the coverage of two biomedical ontologies focusing on diseases with respect to Wikidata for 9 European languages (Czech, Dutch, English, French, German, Italian, Polish, Portuguese and Spanish) for both ontologies, plus Arabic, Chinese and Russian for the second one. We first use direct links between Wikidata and the studied ontologies and then use second-order links by going through other intermediate ontologies. We then compare the quality of the translations obtained thanks to Wikidata with a commercial machine translation tool, here Google Cloud Translation.

Mots clés: biomedical; ontology; translation; wikidata

Domaines: Informatique et langage [cs.CL]; Recherche d'information [cs.IR]; Bio-informatique [q-bio.QM]; Web

Léo Bouscarrat, Antoine Bonnefoy, Cécile Capponi, Carlos Ramisch. Multilingual enrichment of disease biomedical ontologies. Proceedings of the LREC 2020 Workshop on Multilingual Biomedical Text Processing (MultilingualBIO 2020), May 2020, Marseille, France. pp.21-28. ⟨hal-02531140⟩