Ossetic-COT: Designing a morphologically annotated corpus and morphological analyzer for Ossetic
arXiv:2607.04895v2 Announce Type: replace 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%.
The proliferation of advanced AI models has driven demand for high-quality linguistic data, particularly for lesser-resourced languages, to ensure broader inclusivity and technological parity.
This development represents a critical step in making advanced AI accessible to languages with limited digital footprints, enabling the development of language-specific AI applications and preserving linguistic diversity.
The creation of a morphologically annotated corpus and analyzer for Ossetic facilitates the integration of this language into contemporary AI frameworks, potentially reducing the digital divide for Ossetic speakers.
- · Ossetic-speaking communities
- · Linguistic AI developers
- · Cultural preservation initiatives
- · Computational linguists
- · Monolingual AI ecosystems
- · Those reliant on existing language data disparities
The new corpus and analyzer will enable the creation of more sophisticated AI tools for Ossetic, such as better translation, voice recognition, and content generation.
Improved AI capabilities for Ossetic could foster enhanced digital engagement and education within Ossetic-speaking regions, strengthening cultural autonomy.
This effort could inspire similar initiatives for other under-resourced languages, collectively fostering a more linguistically diverse and equitable global AI landscape.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.CL