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A Natural Language Processing Pipeline to Extract Phenotypic Data from Formal Taxonomic Descriptions with a Focus on Flagellate Plants
2018
International Conference on Biomedical Ontology
Assembling large-scale phenotypic datasets for evolutionary and biodiversity studies of plants can be extremely difficult and time consuming. New semi-automated Natural Language Processing (NLP) pipelines can extract phenotypic data from taxonomic descriptions, and their performance can be enhanced by incorporating information from ontologies, like the Plant Ontology (PO) and the Plant Trait Ontology (TO). These ontologies are powerful tools for comparing phenotypes across taxa for large-scale
dblp:conf/icbo/EndaraBCJLC18
fatcat:7xto7a3yezgu3dnepwenwdqudu