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Generation of Abstract Meaning Representations by Hyperedge Replacement Grammars – A Case Study
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The abstract meaning representation (AMR) is a graph-based semantic representation of a natural language sentence that has been the target of numerous studies – in particular, a collection of such graphs over a small domain including the words boy, girl, want and believe has been presented. We investigate the suitability of two hyperedge replacement grammar based formalisms for the generation of AMRs in the form of a case study using the aforementioned boy-girl domain. The first formalism is predictive top-down parsable grammars and the second one is restricted directed acyclic graph grammars; we argue that the latter is more suitable in this limited case. Furthermore, we claim that the domain must be extended in order to draw further conclusions, and that other formalisms should then be considered since both grammar types evaluated here show signs of not being able to handle the generation of AMRs in general. Moreover, we provide a correctness proof for one of the grammars used in this study.

Place, publisher, year, edition, pages
2016. , 50 p.
Series
UMNAD, 1077
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-128415OAI: oai:DiVA.org:umu-128415DiVA: diva2:1051989
Educational program
Master of Science Programme in Computing Science and Engineering
Supervisors
Examiners
Available from: 2016-12-06 Created: 2016-12-05 Last updated: 2016-12-06Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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