1. Create text-to-class map annotator:
Develop a tool or feature that enables users to map text segments to specific classes within the ontology or Body of Knowledge. This annotator facilitates the process of annotating textual content with relevant concepts or entities, streamlining the creation of semantic annotations within the knowledge graph ecosystem.
2. Load from text or load from PDF that is available in Learning Material:
Provide users with the option to load textual content from either plain text files or PDF documents available within the Learning Material repository. This functionality offers flexibility in sourcing textual data for annotation, accommodating different formats and sources to suit user preferences and requirements.
3. Click to generate annotations:
Initiate the annotation process by clicking on the designated button to generate annotations for the loaded text content. This action triggers the text-to-class mapping algorithm to analyze the textual data and identify relevant concepts or entities within the ontology or Body of Knowledge, generating annotations based on semantic associations and relevance.
4. Click on the annotation mark to open annotation info:
Interact with annotation marks displayed on the canvas to add them to the annotation canvas for further refinement or visualization. This feature allows users to review and select annotations for inclusion in the annotation canvas, facilitating the creation of annotated visual representations that capture the semantic relationships between textual content and ontological concepts. By clicking on annotation marks, users can populate the annotation canvas with mapped concepts, enabling comprehensive semantic annotation and knowledge representation within the knowledge graph ecosystem.