On German-2 and Swedish-2, the Word-Char+ tagger is able to reach better results than the reported reference values except for Czech which uses a morphologically fine-grained tagset.
language-∆ to reference tagger Corpus Id # Tags Acc (%) HunPos CRF Word-Char+ Czech 1,574 95.9 -4.7 -3.2 -1.5 German-2 54 97.6 -0.1 -0.2 0.9 Swedish-2 153 96.1 0.0 -0.6 0.1 Table 4: Results of reproducing setups in the literature using the full corpus size fitted PoS taggers reach better results than neural networks when training models on corpora with extremely fine-grained PoS tagsets.