UzUDT: Uzbek Universal Dependencies Treebank

Abstract

In this paper, we present a new Universal Dependencies treebank for Uzbek language(UzUDT) developed as a gold-standard resource with full manual annotation. The treebank includes 684 sentences (7,582 tokens) from Uzbek literary texts, and is larger and more domain-diverse than the existing Uzbek UD treebank. The corpus was developed through rigorous multi-annotator adjudication, achieving very high inter-annotator agreement (multi-rater agreement coefficients >0.90) across lemmatization, PoS tagging, and morphological features. Alongside comprehensive corpus profiling, we establish robust computational baselines by evaluating graph-based (Stanza) and transition-based (spaCy) parsing architectures using both static and monolingual contextual embeddings. Our evaluations reveal a critical architectural trade-off for low-resource agglutinative parsing: joint transition-based models excel at morphosyntactic tagging, whereas graph-based models remain strictly superior for resolving complex structural dependencies. Furthermore, we demonstrate that cross-treebank data augmentation yields substantial, synergistic accuracy gains. The resource provides a much-needed high-quality treebank for Uzbek to assist in developing better NLP tools and to enable linguistic research in the low-resource language

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