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Adapting a parser to clinical text by simple pre-processing rules
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2013 (English)In: Proceedings of the 2013 Workshop on Biomedical Natural Language Processing, Association for Computational Linguistics, 2013, 98-101 p.Conference paper (Refereed)
Abstract [en]

Sentence types typical to Swedish clinical text were extracted by comparing sentence part-of-speech tag sequences in clinical and in standard Swedish text. Parsings by a syntactic dependency parser, trained on standard Swedish, were manually analysed for the 33 sentence types most typical to clinical text. This analysis resulted in the identification of eight error types, and for two of these error types, pre- processing rules were constructed to improve the performance of the parser. For all but one of the ten sentence types affected by these two rules, the parsing was improved by pre-processing.

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2013. 98-101 p.
National Category
Information Systems
Research subject
Computer and Systems Sciences
URN: urn:nbn:se:su:diva-95574ISBN: 978-1-937284-54-1OAI: diva2:660881
Workshop on Biomedical Natural Language Processing (BioNLP 2013), Sofia, Bulgaria, August 4-9 2013
Available from: 2013-10-31 Created: 2013-10-31 Last updated: 2013-11-06Bibliographically approved

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Skeppstedt, Maria
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Department of Computer and Systems Sciences
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ReferencesLink to record
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