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Abstract:In this work we present the first morphologically annotated corpus for Iron Ossetic that conforms to the Universal Dependencies schema. The corpus includes 5454 manually annotated sentences from the Iron Ossetic Corpus of Oral Texts, containing 74032 tokens. We use this corpus to train a BERT-based morphological analyzer. The analyzer achieves tag accuracy of 95.60%.
* Computational Linguistics and Intellectual Technologies. Proceedings of the International Conference Dialogue 2026 (2026) 544-555 * 12 pages