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--- |
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languages: |
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- sr |
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licenses: |
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- cc-by-sa-4.0 |
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task_categories: |
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- structure-prediction |
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|
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task_ids: |
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- tokenization |
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- normalization |
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- part-of-speech-tagging |
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- lemmatization |
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- named-entity-recognition |
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--- |
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The dataset contains 5462 training samples (tweets), 711 validation samples and 725 test samples. |
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Each sample represents a sentence and includes the following features: sentence ID ('sent\_id'), |
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list of tokens ('tokens'), list of normalised tokens ('norms'), list of lemmas ('lemmas'), list of UPOS tags ('upos\_tags'), |
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list of Multext-East tags ('xpos\_tags), list of morphological features ('feats'), |
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and list of IOB tags ('iob\_tags'), which are encoded as class labels. |
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If you are using this dataset in your research, please cite the following paper: |
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|
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``` |
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@article{Miličević_Ljubešić_2016, |
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title={Tviterasi, tviteraši or twitteraši? Producing and analysing a normalised dataset of Croatian and Serbian tweets}, |
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volume={4}, |
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url={https://revije.ff.uni-lj.si/slovenscina2/article/view/7007}, |
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DOI={10.4312/slo2.0.2016.2.156-188}, |
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number={2}, |
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journal={Slovenščina 2.0: empirical, applied and interdisciplinary research}, |
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author={Miličević, Maja and Ljubešić, Nikola}, |
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year={2016}, |
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month={Sep.}, |
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pages={156–188} } |
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``` |
