CoBaLDParser: Joint Morphosyntactic and Semantic Annotation
Ilia Baiuk, Alexandra Baiuk, Maria Petrova · Computational Linguistics and Intellectual Technologies · 2025
Dependency parsing is a common task for modern NLP, and Universal Dependencies (De Marneffe et al., 2021) is widely acknowledged nowadays as a morphosyntactic annotation standard.Yet, its dependency relations are rather generalized, therefore, in order to take more syntactic details into account, the Enhanced UD standard was proposed.A newly developed CoBaLD annotation standard elaborates the E-UD principles by enriching it with the semantic level.It is aimed at structural simplicity and the compatibility with UD in all possible issues.Currently, there are several datasets annotated in CoBaLD standard, but until now, there has been no appropriate tool for automatic data parsing in CoBaLD format.In this paper, we present a neural-based joint parser capable of automatic annotation both in E-UD and in CoBaLD, including ellipsis restoration which is supposed by these standards.Additionally, we provide a qualitative analysis of automatic annotation errors.