A two-stage registry-anchored approach for precision improvement in organization name recognition from PubMed affiliation strings: a validation study

10.7910/DVN/M5PRZB Kang, Inmo Inmo Kang https://orcid.org/0009-0009-9244-6360 Graduate School of Management of Technology, Sogang Univeristy, Seoul, Korea Park, Joonmo Joonmo Park https://orcid.org/0009-0007-5917-5701 Jeong, Heesoo Heesoo Jeong https://orcid.org/0009-0005-9592-8788 Chung, Seyoung Seyoung Chung https://orcid.org/0009-0006-0037-1065 Jeon, Changmin Changmin Jeon https://orcid.org/0009-0000-0711-1158 Moon, Seongwuk Seongwuk Moon https://orcid.org/0000-0003-0375-533X A two-stage registry-anchored approach for precision improvement in organization name recognition from PubMed affiliation strings: a validation study Harvard Dataverse 2026 Social Sciences Moon, Seongwuk Seongwuk Moon Sogang University, Seoul, Korea 2026-02-04 2026-02-04 2026-02-05 16368830 144969 165417 145280 10177 27951904 text/comma-separated-values application/pdf application/pdf application/pdf application/json application/json 2.0 Creative Commons CC0 1.0 Universal Public Domain Dedication. Dataset 1. The dataset analyzed during the current study.