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
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- Linköping University Electronic Press
- Note:
- Pages:
- 164–174
- Language:
- URL:
- https://aclanthology.org/W19-6118
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W19-6118.pdf