The paper examines the use of comparable corpora for contrastive research on the category of nominal number across three languages—English, Czech, and Greek. Two objectives are pursued: a cross-linguistic analysis of number and an assessment of the impact of automatic annotation on linguistic findings. For this study, corpora of comparable size and composition were compiled for the three languages from the Leipzig Corpora Collection. The data were automatically annotated using two open-access tools, Stanza and UDPipe, producing six datasets (two per language), each containing about 5 million sentences and 100 million tokens. Although derived from the same source, the paired datasets for each language differ in sentence and word segmentation, in the number of nouns identified, and in the number values assigned. These differences, nevertheless, do not appear to substantially affect the overall picture of number in the languages examined. The distribution of lemmas by the ratio of singular and plural forms challenges the view commonly presented in grammars that most nouns occur in both numbers and that singular-only and plural-only nouns are rare. However, a closer analysis of nouns assumed to have defective number indicates that answers to more nuanced questions vary depending on the annotation tool used.

UD_Greek-GUD (GUD) is the most recent Universal Dependencies (UD) treebank for Standard Modern Greek (SMG) and the first SMG UD treebank to annotate Verbal Multiword Expressions (VMWEs). GUD contains material from fiction texts and various sites that use colloquial SMG. We describe the special annotation decisions we implemented with GUD, the pipeline we developed to facilitate the active annotation of new material, and we report on the method we designed to evaluate the performance of models trained on GUD as regards VMWE identification tasks.