  We present an analysis on the effect UPOS accuracy has on parsing
performance. Results suggest that leveraging UPOS tags as features for neural
parsers requires a prohibitively high tagging accuracy and that the use of gold
tags offers a non-linear increase in performance, suggesting some sort of
exceptionality. We also investigate what aspects of predicted UPOS tags impact
parsing accuracy the most, highlighting some potentially meaningful linguistic
facets of the problem.
