  We present CorPipe, the winning entry to the CRAC 2023 Shared Task on
Multilingual Coreference Resolution. Our system is an improved version of our
earlier multilingual coreference pipeline, and it surpasses other participants
by a large margin of 4.5 percent points. CorPipe first performs mention
detection, followed by coreference linking via an antecedent-maximization
approach on the retrieved spans. Both tasks are trained jointly on all
available corpora using a shared pretrained language model. Our main
improvements comprise inputs larger than 512 subwords and changing the mention
decoding to support ensembling. The source code is available at
https://github.com/ufal/crac2023-corpipe.
