title: Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.
abstract: BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net.
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA comeau@ncbi.nlm.nih.gov.
authors.forename: Donald C
authors.initials: DC
authors.lastname: Comeau
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: Haibin
authors.initials: H
authors.lastname: Liu
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: Rezarta
authors.initials: R
authors.lastname: Islamaj Doğan
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: W John
authors.initials: WJ
authors.lastname: Wilbur
mesh_terms: D064229:Biological Ontologies; D019295:Computational Biology; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D004194:Disease; D006801:Humans; D009323:Natural Language Processing; D014481:United States