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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.ORCID iD: 0000-0001-8503-0118
University of Edinburgh, United Kingdom.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-7349-7693
University of Padova, Italy.
2021 (English)In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 870, p. 3-28Article in journal (Refereed) Published
Abstract [en]

We develop a finite-state transducer for translating unranked trees into general graphs. This work is motivated by recent progress in semantic parsing for natural language, where sentences are first mapped into tree-shaped syntactic representations, and then these trees are translated into graph semantic representations. We investigate formal properties of our tree-to-graph transducers and develop a polynomial time algorithm for translating a weighted language of input trees into a packed representation, from which best-score graphs can be efficiently recovered.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 870, p. 3-28
Keywords [en]
Semantic graph, Semantic parsing, Tree-to-graph transduction, Weighted automaton
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-213424DOI: 10.1016/j.tcs.2020.12.012Scopus ID: 2-s2.0-85099124542OAI: oai:DiVA.org:umu-213424DiVA, id: diva2:1791352
Available from: 2023-08-25 Created: 2023-08-25 Last updated: 2023-08-25Bibliographically approved

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Björklund, JohannaDrewes, Frank

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
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