A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

BACKGROUND: We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named e...

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Detalles Bibliográficos
Autores principales: Verspoor, Karin, Cohen, Kevin Bretonnel, Lanfranchi, Arrick, Warner, Colin, Johnson, Helen L, Roeder, Christophe, Choi, Jinho D, Funk, Christopher, Malenkiy, Yuriy, Eckert, Miriam, Xue, Nianwen, Baumgartner, William A, Bada, Michael, Palmer, Martha, Hunter, Lawrence E
Formato: Artigo
Lenguaje:Inglês
Publicado: BioMed Central 2012
Materias:
Research Article
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC3483229/
https://ncbi.nlm.nih.gov/pubmed/22901054
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-13-207
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