Adapting Definition Modeling for New Languages: A Case Study on Belarusian
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912479232131072 |
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| author | Kazakouskaya, Daniela Mickus, Timothee Siewert, Janine |
| author_facet | Kazakouskaya, Daniela Mickus, Timothee Siewert, Janine |
| contents | Definition modeling, the task of generating new definitions for words in context, holds great prospect as a means to assist the work of lexicographers in documenting a broader variety of lects and languages, yet much remains to be done in order to assess how we can leverage pre-existing models for as-of-yet unsupported languages. In this work, we focus on adapting existing models to Belarusian, for which we propose a novel dataset of 43,150 definitions. Our experiments demonstrate that adapting a definition modeling systems requires minimal amounts of data, but that there currently are gaps in what automatic metrics do capture. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_09536 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Adapting Definition Modeling for New Languages: A Case Study on Belarusian Kazakouskaya, Daniela Mickus, Timothee Siewert, Janine Computation and Language Definition modeling, the task of generating new definitions for words in context, holds great prospect as a means to assist the work of lexicographers in documenting a broader variety of lects and languages, yet much remains to be done in order to assess how we can leverage pre-existing models for as-of-yet unsupported languages. In this work, we focus on adapting existing models to Belarusian, for which we propose a novel dataset of 43,150 definitions. Our experiments demonstrate that adapting a definition modeling systems requires minimal amounts of data, but that there currently are gaps in what automatic metrics do capture. |
| title | Adapting Definition Modeling for New Languages: A Case Study on Belarusian |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2507.09536 |