In this study, we propose a morpheme-based scheme for Korean dependency
parsing and adopt the proposed scheme to Universal Dependencies. We present the
linguistic rationale that illustrates the motivation and the necessity of
adopting the morpheme-based format, and develop scripts that convert between
the original format used by Universal Dependencies and the proposed
morpheme-based format automatically. The effectiveness of the proposed format
for Korean dependency parsing is then testified by both statistical and neural
models, including UDPipe and Stanza, with our carefully constructed
morpheme-based word embedding for Korean. morphUD outperforms parsing results
for all Korean UD treebanks, and we also present detailed error analyses.Comment: COLING2022, Poste