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The CLIN27 Shared Task: Translating Historical Text to Contemporary Language for Improving Automatic Linguistic Annotation
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2017 (English)In: Computational Linguistics in the Netherlands Journal, ISSN 2211-4009, Vol. 7, p. 53-64Article in journal (Refereed) Published
Abstract [en]

The CLIN27 shared task evaluates the effect of translating historical text to modern text with the goal of improving the quality of the output of contemporary natural language processing tools applied to the text. We focus on improving part-of-speech tagging analysis of seventeenth-century Dutch. Eight teams took part in the shared task. The best results were obtained by teams employing character-based machine translation. The best system obtained an error reduction of 51% in comparison with the baseline of tagging unmodified text. This is close to the error reduction obtained by human translation (57%).

Place, publisher, year, edition, pages
2017. Vol. 7, p. 53-64
Keywords [en]
historical text, text normalization, neural networks, machine translation, dutch language
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:su:diva-148207OAI: oai:DiVA.org:su-148207DiVA, id: diva2:1150182
Available from: 2017-10-18 Created: 2017-10-18 Last updated: 2018-05-17Bibliographically approved

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Östling, RobertScherrer, YvesTiedemann, Jörg
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CiteExportLink to record
Permanent link

Direct link
Cite
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
  • rtf