title: The CLEF corpus: semantic annotation of clinical text.
abstract: The Clinical E-Science Framework (CLEF) project is building a framework for the capture, integration and presentation of clinical information: for clinical research, evidence-based health care and genotype-meets-phenotype informatics. A significant portion of the information required by such a framework originates as text, even in EHR-savvy organizations. CLEF uses Information Extraction (IE) to make this unstructured information available. An important part of IE is the identification of semantic entities and relationships. Typical approaches require human annotated documents to provide both evaluation standards and material for system development. CLEF has a corpus of clinical narratives, histopathology reports and imaging reports from 20 thousand patients. We describe the selection of a subset of this corpus for manual annotation of clinical entities and relationships. We describe an annotation methodology and report encouraging initial results of inter-annotator agreement. Comparisons are made between different text sub-genres, and between annotators with different skills.
authors.affiliation: Natural Language Processing Group, University of Sheffield, UK.
authors.forename: Angus
authors.initials: A
authors.lastname: Roberts
authors.forename: Robert
authors.initials: R
authors.lastname: Gaizauskas
authors.forename: Mark
authors.initials: M
authors.lastname: Hepple
authors.forename: Neil
authors.initials: N
authors.lastname: Davis
authors.forename: George
authors.initials: G
authors.lastname: Demetriou
authors.forename: Yikun
authors.initials: Y
authors.lastname: Guo
authors.forename: Jay
authors.initials: J
authors.lastname: Kola
authors.forename: Ian
authors.initials: I
authors.lastname: Roberts
authors.forename: Andrea
authors.initials: A
authors.lastname: Setzer
authors.forename: Archana
authors.initials: A
authors.lastname: Tapuria
authors.forename: Bill
authors.initials: B
authors.lastname: Wheeldin
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D012660:Semantics