FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers

Simon Mille, Roberto Carlini, Alicia Burga, Leo Wanner


Abstract
We present the contribution of Universitat Pompeu Fabra’s NLP group to the SemEval Task 9.2 (AMR-to-English Generation). The proposed generation pipeline comprises: (i) a series of rule-based graph-transducers for the syntacticization of the input graphs and the resolution of morphological agreements, and (ii) an off-the-shelf statistical linearization component.
Anthology ID:
S17-2158
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
920–923
Language:
URL:
https://aclanthology.org/S17-2158
DOI:
10.18653/v1/S17-2158
Bibkey:
Cite (ACL):
Simon Mille, Roberto Carlini, Alicia Burga, and Leo Wanner. 2017. FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 920–923, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
FORGe at SemEval-2017 Task 9: Deep sentence generation based on a sequence of graph transducers (Mille et al., SemEval 2017)
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PDF:
https://aclanthology.org/S17-2158.pdf