This paper introduces UniDive for Korean, an integrated framework that bridges Universal Dependencies (UD) and Universal Morphology (UniMorph) to enhance the representation and processing of Korean {morphosyntax}. Korean's rich inflectional morphology and flexible word order pose challenges for existing frameworks, which often treat morphology and syntax separately, leading to inconsistencies in linguistic analysis. UniDive unifies syntactic and morphological annotations by preserving syntactic dependencies while incorporating UniMorph-derived features, improving consistency in annotation. We construct an integrated dataset and apply it to dependency parsing, demonstrating that enriched morphosyntactic features enhance parsing accuracy, particularly in distinguishing grammatical relations influenced by morphology. Our experiments, conducted with both encoder-only and decoder-only models, confirm that explicit morphological information contributes to more accurate syntactic analysis.

翻译：本文提出针对韩语的UniDive框架，该集成化框架通过桥接通用依存关系（UD）与通用形态学（UniMorph）体系，以提升韩语形态句法结构的表示与处理能力。韩语丰富的屈折形态与灵活语序对现有框架构成挑战——这些框架通常将形态学与句法学割裂处理，导致语言分析存在不一致性。UniDive通过保留句法依存关系的同时整合UniMorph衍生的特征，实现了句法与形态标注的统一，提升了标注一致性。我们构建了集成化数据集并将其应用于依存句法分析，实验表明增强的形态句法特征能有效提升句法分析准确率，尤其在区分受形态影响的语法关系方面效果显著。通过编码器专用模型与解码器专用模型的对比实验，我们验证了显式形态信息能够促进更精确的句法分析。