  Named Entity Recognition (NER) is a fundamental NLP tasks with a wide range
of practical applications. The performance of state-of-the-art NER methods
depends on high quality manually anotated datasets which still do not exist for
some languages. In this work we aim to remedy this situation in Slovak by
introducing WikiGoldSK, the first sizable human labelled Slovak NER dataset. We
benchmark it by evaluating state-of-the-art multilingual Pretrained Language
Models and comparing it to the existing silver-standard Slovak NER dataset. We
also conduct few-shot experiments and show that training on a sliver-standard
dataset yields better results. To enable future work that can be based on
Slovak NER, we release the dataset, code, as well as the trained models
publicly under permissible licensing terms at
https://github.com/NaiveNeuron/WikiGoldSK.
