The problem with probabilistic DAG automata for semantic graphs

Ieva Vasiljeva, Sorcha Gilroy, Adam Lopez


Abstract
Semantic representations in the form of directed acyclic graphs (DAGs) have been introduced in recent years, and to model them, we need probabilistic models of DAGs. One model that has attracted some attention is the DAG automaton, but it has not been studied as a probabilistic model. We show that some DAG automata cannot be made into useful probabilistic models by the nearly universal strategy of assigning weights to transitions. The problem affects single-rooted, multi-rooted, and unbounded-degree variants of DAG automata, and appears to be pervasive. It does not affect planar variants, but these are problematic for other reasons.
Anthology ID:
N19-1096
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
902–911
Language:
URL:
https://aclanthology.org/N19-1096
DOI:
10.18653/v1/N19-1096
Bibkey:
Cite (ACL):
Ieva Vasiljeva, Sorcha Gilroy, and Adam Lopez. 2019. The problem with probabilistic DAG automata for semantic graphs. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 902–911, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
The problem with probabilistic DAG automata for semantic graphs (Vasiljeva et al., NAACL 2019)
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PDF:
https://aclanthology.org/N19-1096.pdf