  We evaluate the efficacy of predicted UPOS tags as input features for
dependency parsers in lower resource settings to evaluate how treebank size
affects the impact tagging accuracy has on parsing performance. We do this for
real low resource universal dependency treebanks, artificially low resource
data with varying treebank sizes, and for very small treebanks with varying
amounts of augmented data. We find that predicted UPOS tags are somewhat
helpful for low resource treebanks, especially when fewer fully-annotated trees
are available. We also find that this positive impact diminishes as the amount
of data increases.
