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Bottom-up unranked tree-to-graph transducers for translation into semantic graphs
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)ORCID iD: 0000-0001-8503-0118
University of Edinburgh.
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)ORCID iD: 0000-0001-7349-7693
University of Padova.
2019 (English)In: Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing / [ed] Heiko Vogler; Andreas Maletti, Association for Computational Linguistics, 2019, p. 7-17, article id W19-3104Conference paper, Published paper (Refereed)
Abstract [en]

We propose a formal model for translating unranked syntactic trees, such as dependency trees, into semantic graphs. These tree-to-graph transducers can serve as a formal basis of transition systems for semantic parsing which recently have been shown to perform very well, yet hitherto lack formalization. Our model features "extended" rules and an arc-factored normal form, comes with an efficient translation algorithm, and can be equipped with weights in a straightforward manner.

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2019. p. 7-17, article id W19-3104
National Category
Computer Sciences Natural Language Processing
Research subject
Computer Science; computational linguistics
Identifiers
URN: urn:nbn:se:umu:diva-162561OAI: oai:DiVA.org:umu-162561DiVA, id: diva2:1344873
Conference
The 14th International Conference on Finite-State Methods and Natural Language Processing, FSMNLP, Dresden, Germany, September 23–25, 2019
Available from: 2019-08-22 Created: 2019-08-22 Last updated: 2025-02-01Bibliographically approved

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Björklund, JohannaDrewes, Frank

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Citation style
  • apa
  • ieee
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  • Other style
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf