  We present K{\o}psala, the Copenhagen-Uppsala system for the Enhanced
Universal Dependencies Shared Task at IWPT 2020. Our system is a pipeline
consisting of off-the-shelf models for everything but enhanced graph parsing,
and for the latter, a transition-based graph parser adapted from Che et al.
(2019). We train a single enhanced parser model per language, using gold
sentence splitting and tokenization for training, and rely only on tokenized
surface forms and multilingual BERT for encoding. While a bug introduced just
before submission resulted in a severe drop in precision, its post-submission
fix would bring us to 4th place in the official ranking, according to average
ELAS. Our parser demonstrates that a unified pipeline is effective for both
Meaning Representation Parsing and Enhanced Universal Dependencies.
