Comparison of Current Approaches to Lemmatization: A Case Study in Estonian
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913326003388416 |
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| author | Dorkin, Aleksei Sirts, Kairit |
| author_facet | Dorkin, Aleksei Sirts, Kairit |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_15003 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Comparison of Current Approaches to Lemmatization: A Case Study in Estonian Dorkin, Aleksei Sirts, Kairit Computation and Language 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. |
| title | Comparison of Current Approaches to Lemmatization: A Case Study in Estonian |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2404.15003 |