Paradigm Clustering with Weighted Edit Distance

Andrew Gerlach, Adam Wiemerslage, Katharina Kann


Abstract
This paper describes our system for the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering, which asks participants to group inflected forms together according their underlying lemma without the aid of annotated training data. We employ agglomerative clustering to group word forms together using a metric that combines an orthographic distance and a semantic distance from word embeddings. We experiment with two variations of an edit distance-based model for quantifying orthographic distance, but, due to time constraints, our system does not improve over the shared task’s baseline system.
Anthology ID:
2021.sigmorphon-1.12
Volume:
Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SIGMORPHON
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
107–114
Language:
URL:
https://aclanthology.org/2021.sigmorphon-1.12
DOI:
10.18653/v1/2021.sigmorphon-1.12
Bibkey:
Cite (ACL):
Andrew Gerlach, Adam Wiemerslage, and Katharina Kann. 2021. Paradigm Clustering with Weighted Edit Distance. In Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 107–114, Online. Association for Computational Linguistics.
Cite (Informal):
Paradigm Clustering with Weighted Edit Distance (Gerlach et al., SIGMORPHON 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.sigmorphon-1.12.pdf