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Towards comprehensive syntactic and semantic annotations of the clinical narrative.
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In: Journal of the American Medical Informatics Association : JAMIA, vol 20, iss 5 (2013)
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Towards comprehensive syntactic and semantic annotations of the clinical narrative
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Albright, Daniel; Lanfranchi, Arrick; Fredriksen, Anwen; Styler, William F; Warner, Colin; Hwang, Jena D; Choi, Jinho D; Dligach, Dmitriy; Nielsen, Rodney D; Martin, James; Ward, Wayne; Palmer, Martha; Savova, Guergana K. - : BMJ Publishing Group, 2013
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Abstract:
Objective: To create annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP). To develop NLP algorithms and open source components. Methods: Manual annotation of a clinical narrative corpus of 127 606 tokens following the Treebank schema for syntactic information, PropBank schema for predicate-argument structures, and the Unified Medical Language System (UMLS) schema for semantic information. NLP components were developed. Results: The final corpus consists of 13 091 sentences containing 1772 distinct predicate lemmas. Of the 766 newly created PropBank frames, 74 are verbs. There are 28 539 named entity (NE) annotations spread over 15 UMLS semantic groups, one UMLS semantic type, and the Person semantic category. The most frequent annotations belong to the UMLS semantic groups of Procedures (15.71%), Disorders (14.74%), Concepts and Ideas (15.10%), Anatomy (12.80%), Chemicals and Drugs (7.49%), and the UMLS semantic type of Sign or Symptom (12.46%). Inter-annotator agreement results: Treebank (0.926), PropBank (0.891–0.931), NE (0.697–0.750). The part-of-speech tagger, constituency parser, dependency parser, and semantic role labeler are built from the corpus and released open source. A significant limitation uncovered by this project is the need for the NLP community to develop a widely agreed-upon schema for the annotation of clinical concepts and their relations. Conclusions: This project takes a foundational step towards bringing the field of clinical NLP up to par with NLP in the general domain. The corpus creation and NLP components provide a resource for research and application development that would have been previously impossible. ; Version of Record
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Keyword:
cTAKES; Gold Standard Annotations; Natural Language Processing; Propbank; Treebank; UMLS
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URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879401
https://doi.org/10.1136/amiajnl-2012-001317
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Chinese Treebank 7.0
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In: broadcast conversation, broadcast news, news magazine, newswire, web collection (2013)
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Using the visual denotations of image captions for semantic inference
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Towards Comprehensive Syntactic and Semantic Annotations of the Clinical Narrative
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In: Journal of the American Medical Informatics Association, 2013. Oxford, UK: Oxford University Press (2013)
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Natural Language Processing to the Rescue? Extracting "Situational Awareness" Tweets During Mass Emergency
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In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 5 No. 1 (2011): Fifth International AAAI Conference on Weblogs and Social Media ; 2334-0770 ; 2162-3449 (2011)
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To Annotate More Accurately or to Annotate More
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In: Fourth Linguistic Annotation Workshop at the Association for Computational Linguistics 2010 Conference. July 15-16, 2010. Uppsala, Sweden. (2010)
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