Before revision:  In this paper, we perform a comparative analysis of both approaches in a variety of settings currently considered in the literature . In particular, we evaluate how well they work when document-level features are leveraged. Our evaluation on the classic CoNLL benchmark datasets for 4 languages shows that document-level features significantly improve NER quality and that fine-tuning generally outperforms the feature-based approaches .
After revision:  In this paper, we perform a comparative analysis of both approaches in a variety of settings currently considered in the literature , namely " fine-tuning generally outperforms the feature-based approaches .