Hybrid Ontology and NLP-Based Annotation Model for Indigenous Lexicon and Folklore Preservation

Abstract

This model combines an ontology with NLP
technology to aid in retaining Indigenous vocabularies and
folklore aimed at low-resource languages. Automatic annotation
and classification of culture-specific narratives is achieved
through semantic web technologies and natural language
processing. Contextual intricacies are preserved culturally and
contextually. The model contains a folklore ontology annotated
with the aid of community and expert volunteers, thereby
ensuring relevancy and accuracy. Case studies on the Uzbek
languages showed enhanced digitization, increased accessibility,
and the semantic understanding of indigenous ontological
knowledge. The study also highlighted contextual digital
preservation addressing resource sensitivity, rare dialectal
variation, and culture-informed context preservation. Future
work includes broadening the Corpora, optimizing the models
for specific dialects, and establishing ethical frameworks for
community-centric preservation initiatives. This will help
resolve concerns about erasing indigenous knowledge while
developing avenues for research on digital heritage
preservation.