A Computational Model of Latvian Morphology

Peteris Paikens, Lauma Pretkalniņa, Laura Rituma


Abstract
In this paper we describe a computational model of Latvian morphology that provides a formal structure for Latvian word form inflection and has been implemented in software for generation, analysis and lemmatization of Latvian word forms. The work was motivated by the need for a NLP inflection model that can cover all the complexity of Latvian language and explicitly enumerate and handle the many exceptions to the general Latvian inflection principles. This is an evolution of earlier work, extending the initial proof of concept model to properly cover Latvian language. We provide a set of morphological paradigms that differ from current linguistic tradition, a set of systematic stem changes and combine it with an extensive lexicon that includes paradigm information and structured morphological attributes for 118 000 lexemes. This model has been applied on both dictionary and corpora data, demonstrating that it provides a good coverage for modern Latvian literary language. We also consider that there is a good potential to extend this also to the related Latgalian language.
Anthology ID:
2024.lrec-main.20
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
221–232
Language:
URL:
https://aclanthology.org/2024.lrec-main.20
DOI:
Bibkey:
Cite (ACL):
Peteris Paikens, Lauma Pretkalniņa, and Laura Rituma. 2024. A Computational Model of Latvian Morphology. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 221–232, Torino, Italia. ELRA and ICCL.
Cite (Informal):
A Computational Model of Latvian Morphology (Paikens et al., LREC-COLING 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.lrec-main.20.pdf