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