UDPipe at SIGMORPHON 2019: Contextualized Embeddings, Regularization with Morphological Categories, Corpora Merging
Table 3: Lemma accuracy, lemma Levenshtein, morphological accuracy, and morphological F1 results of ablation experiments. For comparison, the FT only embeddings denote the pretrained embeddings of Grave et al. (2018).
['Word Embeddings', 'BERT', 'Feature Regularization', 'Lemma Acc', 'Lemma Lev', 'Morph Acc', 'Morph F1']
Even the baseline model without any of the mentioned enhancements achieves relatively high performance and would place third in both lemmatization and tagging accuracy (when not considering our competition entry).