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International Workshop on Controlled Natural Language

CNL 2014: Controlled Natural Language pp 90–101Cite as

FrameNet CNL: A Knowledge Representation and Information Extraction Language

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8625))

Abstract

The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL. The framework is used on natural language documents and represents the extracted knowledge in a tailor-made Frame-ontology from which unambiguous FrameNet-CNL paraphrase text can be generated automatically in multiple languages. This approach brings together the fields of information extraction and CNL, because a source text can be considered belonging to FrameNet-CNL, if information extraction parser produces the correct knowledge representation as a result. We describe a state-of-the-art information extraction parser used by a national news agency and speculate that FrameNet-CNL eventually could shape the natural language subset used for writing the newswire articles.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of Latvia, Rainis blvd. 29, Riga, LV-1459, Latvia

    Guntis Barzdins

Authors
  1. Guntis Barzdins
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Editor information

Editors and Affiliations

  1. Digital Enterprise Research Institute, National University of Ireland, Galway, Ireland

    Brian Davis

  2. Institute of Computational Linguistics, University of Zurich, Switzerland

    Kaarel Kaljurand

  3. Department of Humanities, Social and Political Sciences, ETH Zurich, Switzerland

    Tobias Kuhn

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© 2014 Springer International Publishing Switzerland

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Barzdins, G. (2014). FrameNet CNL: A Knowledge Representation and Information Extraction Language. In: Davis, B., Kaljurand, K., Kuhn, T. (eds) Controlled Natural Language. CNL 2014. Lecture Notes in Computer Science(), vol 8625. Springer, Cham. https://doi.org/10.1007/978-3-319-10223-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-10223-8_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10222-1

  • Online ISBN: 978-3-319-10223-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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