Comparison of Current Approaches to Lemmatization: A Case Study in Estonian
<|reference_start|>Comparison of Current Approaches to Lemmatization: A Case Study in Estonian: 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.<|reference_end|>
@article{dorkin2024comparison,
    title={Comparison of Current Approaches to Lemmatization: A Case Study in
  Estonian},
    author={Aleksei Dorkin and Kairit Sirts},
    journal={Proceedings of the 24th Nordic Conference on Computational
  Linguistics (NoDaLiDa), pp. 280-285, May 2023},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.15003},
    primaryClass={cs.CL}
}