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The Swedish FrameNet++: Harmonization, integration, method development and practical language technology applications
Edited by Dana Dannélls, Lars Borin and Karin Friberg Heppin
[Natural Language Processing 14] 2021
► pp. 69–96

Chapter 3
Swedish FrameNet++ – lexical samsara

 | University of Gothenburg
 | University of Gothenburg
 | Arctic University of Norway
 | University of Gothenburg
One of the main goals of the Swedish FrameNet++ initiative is to recycle and include as many existing modern Swedish lexical resources as possible into one unified lexical macroresource useful for automatic language processing. In this chapter we describe the structure of Saldo, the central resource of Swedish FrameNet++, the design of the formal interlinking mechanism keeping the lexical macroresource together, and our work on Swesaurus, a Swedish wordnet, and a Swedish Roget-style thesaurus as components of Swedish FrameNet++.
Article outline
  • 1.Introduction
  • 2.Saldo: The heart of Swedish FrameNet++
    • 2.1Saldo in a nutshell
    • 2.2The origin of Saldo
    • 2.3The semantic structure of Saldo
    • 2.4Morphological information in Saldo
  • 3.Persistent identifiers: The glue of Swedish FrameNet++
  • 4.Branching out: Lexical semantics galore
    • 4.1The Swesaurus component of Swedish FrameNet++
      • 4.1.1Towards a Swedish wordnet
      • 4.1.2Mining Saldo for classical lexical-semantic relations
      • 4.1.3Synlex
      • 4.1.4Wiktionary
      • 4.1.5Core WordNet
      • 4.1.6The Gothenburg semantic database
      • 4.1.7The state of Swesaurus
    • 4.2Towards a thesaurus component of Swedish FrameNet++
      • 4.2.1Roget’s Thesaurus and language technology
      • 4.2.2Including Bring’s Swedish thesaurus in Swedish FrameNet++
  • 5.Looking forward: New directions up ahead
  • Notes
  • References
Available under the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) 4.0 license.

For any use beyond this license, please contact the publisher at [email protected].

Published online: 26 November 2021
DOI logo
https://doi.org/10.1075/nlp.14.03bor
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