Equiprobable mappings in weighted constraint grammars

Arto Anttila, Scott Borgeson, Giorgio Magri


Abstract
We show that MaxEnt is so rich that it can distinguish between any two different mappings: there always exists a nonnegative weight vector which assigns them different MaxEnt probabilities. Stochastic HG instead does admit equiprobable mappings and we give a complete formal characterization of them.
Anthology ID:
W19-4215
Volume:
Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WS
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
125–134
Language:
URL:
https://aclanthology.org/W19-4215
DOI:
10.18653/v1/W19-4215
Bibkey:
Cite (ACL):
Arto Anttila, Scott Borgeson, and Giorgio Magri. 2019. Equiprobable mappings in weighted constraint grammars. In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 125–134, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Equiprobable mappings in weighted constraint grammars (Anttila et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4215.pdf