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Something Old, Something New: Applying a Pre-trained Parsing Model to Clinical Swedish
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2011 (English)In: 18th Nordic Conference of Computational Linguistics NODALIDA 2011, Riga, Latvia: Northern European Association for Language Technology (NEALT) , 2011Conference paper, Published paper (Refereed)
Abstract [en]

Information access from clinical text is a research area which has gained a large amount of interest in recent years. Automatic syntactic analysis for the creation of deeper language models is potentially very useful for such methods. However, syntactic parsers that are tailored to accommodate for the distinctive properties of clinical language are rare and costly to build. We present an initial study on the applicability of an existing parser, pre-trained on general Swedish, to clinical text in Swedish. We manually evaluate twelve documents and obtain a 92.4% part-of-speech tagging accuracy and a 76.6% labeled attachment score for the syntactic dependency parsing.

Place, publisher, year, edition, pages
Riga, Latvia: Northern European Association for Language Technology (NEALT) , 2011.
National Category
Information Science
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-62355OAI: oai:DiVA.org:su-62355DiVA: diva2:441280
Available from: 2011-09-15 Created: 2011-09-15

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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