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Transition-based Generation from Abstract Meaning Representations
Art der Abschlussarbeit
  • Schick, Timo
  • Prof. Dr.-Ing. habil. Heiko Vogler
This work addresses the task of generating English sentences from Abstract Meaning Representation (AMR) graphs. To cope with this task, we transform each input AMR graph into a structure similar to a dependency tree and annotate it with syntactic information by applying various predefined actions to it. Subsequently, a sentence is obtained from this tree structure by visiting its nodes in a specific order. We train maximum entropy models to estimate the probability of each individual action and devise an algorithm that efficiently approximates the best sequence of actions to be applied. Our generator achieves a Bleu score of 27.4 on the LDC2014T12 test set.
abstract meaning reprsentation, transition, generation
Stand: 26.10.2020 10:29 Uhr