Constructing an Ontology-Driven Knowledge Graph from Unstructured Texts: A Semi-Automatic Methodology Applied to Moroccan Intangible Cultural Heritage

Moroccan ICH is a rich domain that remains difficult to structure formally due to the heterogeneity of textual descriptions and the diversity of documented cultural practices. This article proposes a semi-automatic and adaptable methodological framework for constructing an ontology-driven knowledge graph from unstructured texts, applied to Moroccan ICH. The approach begins by classifying documents into the five predefined UNESCO categories using lexical, semantic, and hybrid methods, followed by intra-category semantic clustering to identify thematic substructures that inform ontological modeling. The results show that hybrid approaches achieve the best performance in document classification, while clustering requires an adaptive strategy for each category. Building on these stages, ICHOnto was generated as a CIDOC CRM-aligned ontology enriched with UNESCO categories, expert-validated subcategories, and entities and relations extracted from the texts. The resulting resource was evaluated through logical consistency, SHACL compliance, and functional assessment using Competency Questions. The evaluation confirms that ICHOnto provides a coherent, exploitable, and interoperable semantic resource for representing, organizing, and querying Moroccan ICH. Its modular structure also supports adaptation to other heritage corpora or domains based on unstructured textual data.