20.500.12556/DiRROS-16510 From language models to large-scale food and biomedical knowledge graphs Knowledge about the interactions between dietary and biomedical factors is scattered throughout uncountable research articles in an unstructured form (e.g., text, images, etc.) and requires automatic structuring so that it can be provided to medical professionals in a suitable format. Various biomedical knowledge graphs exist, however, they require further extension with relations between food and biomedical entities. In this study, we evaluate the performance of three state-of-the-art relation-mining pipelines (FooDis, FoodChem and ChemDis) which extract relations between food, chemical and disease entities from textual data. We perform two case studies, where relations were automatically extracted by the pipelines and validated by domain experts. The results show that the pipelines can extract relations with an average precision around 70%, making new discoveries available to domain experts with reduced human effort, since the domain experts should only evaluate the results, instead of finding, and reading all new scientific papers. biomedical knowledge graphs relation-mining pipelines relation extraction validation biomedicinski grafi znanja true false true Springer Nature Švica Angleški jezik Slovenski jezik Neznano 2023-05-17 12:11:41 2023-05-17 12:11:43 2023-05-18 03:35:51 0000-00-00 00:00:00 2023 0 0 Nasl. z nasl. zaslona; Soavtorji: Lidija Strojnik, Risto Angelski, Nivec Ogrinc, Barbara Koroušić Seljak, Tome Eftimov; Opis vira z dne 17. 5. 2023; str. 1-14 Vol. 13, article no. 7815 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 2023-05-10 2023-05-15 004 2045-2322 0.1038/s41598-023-34981-4 152401411 https://www.nature.com/articles/s41598-023-34981-4 1 79f369d6-f48a-11ed-a314-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=22298 RAZ_Cenikj_Gjorgjina_2023.pdf RAZ_Cenikj_Gjorgjina_2023.pdf 1 FA6D33D9F9BF8BEB3F386B8906D85B8F 4b26c6289f8072ba3b0cbd273c2ee6e22b402d053de618563078f02c32401ebd 52e0754b-f48c-11ed-a314-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=22299 Institut Jožef Stefan 0 0 0