Comparison of Current Approaches to Lemmatization: A Case Study in Estonian
Computation and Language
2024-04-24 v1
Abstract
This study evaluates three different lemmatization approaches to Estonian -- Generative character-level models, Pattern-based word-level classification models, and rule-based morphological analysis. According to our experiments, a significantly smaller Generative model consistently outperforms the Pattern-based classification model based on EstBERT. Additionally, we observe a relatively small overlap in errors made by all three models, indicating that an ensemble of different approaches could lead to improvements.
Keywords
Cite
@article{arxiv.2404.15003,
title = {Comparison of Current Approaches to Lemmatization: A Case Study in Estonian},
author = {Aleksei Dorkin and Kairit Sirts},
journal= {arXiv preprint arXiv:2404.15003},
year = {2024}
}
Comments
6 pages, 2 figures