publication . Article . 2020

Dependency parsing of biomedical text with BERT

Jenna Kanerva; Filip Ginter; Sampo Pyysalo;
Open Access English
  • Published: 01 Dec 2020 Journal: BMC Bioinformatics, volume 21, pages 1-12 (issn: 1471-2105, Copyright policy)
  • Publisher: BMC
Abstract
<jats:title>Abstract</jats:title><jats:sec> <jats:title>Background: </jats:title> <jats:p>Syntactic analysis, or parsing, is a key task in natural language processing and a required component for many text mining approaches. In recent years, Universal Dependencies (UD) has emerged as the leading formalism for dependency parsing. While a number of recent tasks centering on UD have substantially advanced the state of the art in multilingual parsing, there has been only little study of parsing texts from specialized domains such as biomedicine.</jats:p> </jats:sec><jats:sec> <jats:title>Methods: </jats:title> <jats:p>We explore the application of state-of-the-art n...
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Subjects
free text keywords: Parsing, Deep learning, CRAFT, Research, Biochemistry, Applied Mathematics, Molecular Biology, Structural Biology, Computer Science Applications, lcsh:Computer applications to medicine. Medical informatics, lcsh:R858-859.7, lcsh:Biology (General), lcsh:QH301-705.5, Parsing, computer.software_genre, computer, Natural language processing, Transfer of learning, Artificial intelligence, business.industry, business, Computer science, Biomedicine, Deep learning, Initialization, Dependency grammar, Biomedical text, Formalism (philosophy)
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