BELHD: improving biomedical entity linking with homonym disambiguation.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Biomedical entity linking (BEL) is the task of grounding entity mentions to a given knowledge base (KB). Recently, neural name-based methods, system identifying the most appropriate name in the KB for a given mention using neural network (either via dense retrieval or autoregressive modeling), achieved remarkable results for the task, without requiring manual tuning or definition of domain/entity-specific rules. However, as name-based methods directly return KB names, they cannot cope with homonyms, i.e. different KB entities sharing the exact same name. This significantly affects their performance for KBs where homonyms account for a large amount of entity mentions (e.g. UMLS and NCBI Gene).

Authors

  • Samuele Garda
    Computer Science, Humboldt-Universität zu Berlin, Berlin 12489, Germany.
  • Ulf Leser
    Humboldt-Universität zu Berlin, Knowledge Management in Bioinformatics, Berlin, Germany.