  We present the Uppsala system for the CoNLL 2018 Shared Task on universal
dependency parsing. Our system is a pipeline consisting of three components:
the first performs joint word and sentence segmentation; the second predicts
part-of- speech tags and morphological features; the third predicts dependency
trees from words and tags. Instead of training a single parsing model for each
treebank, we trained models with multiple treebanks for one language or closely
related languages, greatly reducing the number of models. On the official test
run, we ranked 7th of 27 teams for the LAS and MLAS metrics. Our system
obtained the best scores overall for word segmentation, universal POS tagging,
and morphological features.
