Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER
Table 1: Size of morphological and analytical annotations of PDT 3.5 train/development/test sets.
['Part', 'Morphological m-layer Words', 'Morphological m-layer Sentences', 'Analytical a-layer Words', 'Analytical a-layer Sentences']
Prague Dependency Treebank 3.5 The Prague Dependency Treebank 3.5 The Prague Dependency Treebank 3.5 contains the same texts as the previous versions since 2.0, and is divided into train, dtest, and etest subparts, where dtest is used as a development set and etest as a test set. The dataset consists of several layers – the morphological m-layer is the largest and contains morphological annotations (POS tags and lemmas), the analytical a-layer contains labeled dependency trees, and the t-layer is the smallest and contains tectogrammatical trees. Both UAS and LAS are also better on the UD treebank, which we assume is caused by the different annotation scheme.