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---
languages:
- sr
licenses:
- cc-by-sa-4.0
task_categories:
- structure-prediction
task_ids:
- tokenization
- normalization
- part-of-speech-tagging
- lemmatization
- named-entity-recognition
---
This dataset is based on 6,898 Serbian tweets that were segmented into sentences, tokens, and annotated with normalized forms, lemmas, MULTEXTEast tags (XPOS), UPOS tags and morphological features, and named entities.
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 named entity 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} }
``` |