Tina Munda
2024
SUK 1.0: A New Training Corpus for Linguistic Annotation of Modern Standard Slovene
Špela Arhar Holdt
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Jaka Čibej
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Kaja Dobrovoljc
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Tomaž Erjavec
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Polona Gantar
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Simon Krek
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Tina Munda
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Nejc Robida
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Luka Terčon
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Slavko Zitnik
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
This paper introduces the upgrade of a training corpus for linguistic annotation of modern standard Slovene. The enhancement spans both the size of the corpus and the depth of annotation layers. The revised SUK 1.0 corpus, building on its predecessor ssj500k 2.3, has doubled in size, containing over a million tokens. This expansion integrates three preexisting open-access datasets, all of which have undergone automatic tagging and meticulous manual review across multiple annotation layers, each represented in varying proportions. These layers span tokenization, segmentation, lemmatization, MULTEXT-East morphology, Universal Dependencies, JOS-SYN syntax, semantic role labeling, named entity recognition, and the newly incorporated coreferences. The paper illustrates the annotation processes for each layer while also presenting the results of the new CLASSLA-Stanza annotation tool, trained on the SUK corpus data. As one of the fundamental language resources of modern Slovene, the SUK corpus calls for constant development, as outlined in the concluding section.
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Co-authors
- Špela Arhar Holdt 1
- Jaka Čibej 1
- Kaja Dobrovoljc 1
- Tomaž Erjavec 1
- Polona Gantar 1
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