  Machine translation (MT) has almost achieved human parity at sentence-level
translation. In response, the MT community has, in part, shifted its focus to
document-level translation. However, the development of document-level MT
systems is hampered by the lack of parallel document corpora. This paper
describes BWB, a large parallel corpus first introduced in Jiang et al. (2022),
along with an annotated test set. The BWB corpus consists of Chinese novels
translated by experts into English, and the annotated test set is designed to
probe the ability of machine translation systems to model various discourse
phenomena. Our resource is freely available, and we hope it will serve as a
guide and inspiration for more work in document-level machine translation.
