Inferring morphological rules from small examples using 0/1 linear programming

Ann Lillieström, Koen Claessen, Nicholas Smallbone


Abstract
We show how to express the problem of finding an optimal morpheme segmentation from a set of labelled words as a 0/1 linear programming problem, and how to build on this to analyse a language’s morphology. The approach works even when there is very little training data available.
Anthology ID:
W19-6118
Volume:
Proceedings of the 22nd Nordic Conference on Computational Linguistics
Month:
September–October
Year:
2019
Address:
Turku, Finland
Editors:
Mareike Hartmann, Barbara Plank
Venue:
NoDaLiDa
SIG:
Publisher:
Linköping University Electronic Press
Note:
Pages:
164–174
Language:
URL:
https://aclanthology.org/W19-6118
DOI:
Bibkey:
Cite (ACL):
Ann Lillieström, Koen Claessen, and Nicholas Smallbone. 2019. Inferring morphological rules from small examples using 0/1 linear programming. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 164–174, Turku, Finland. Linköping University Electronic Press.
Cite (Informal):
Inferring morphological rules from small examples using 0/1 linear programming (Lillieström et al., NoDaLiDa 2019)
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PDF:
https://aclanthology.org/W19-6118.pdf