SAGE (a Semantic Annotator for knowledge Graph Exploration) is a “Thing” annotation system. Here, “Thing” refers to any concept, named individuals (aka entities), entity relations, and attributes. The system is primarily built based on the idea of “string to thing” where the “string” is any given text (e.g., abstract of an article) as input by the user. For annotation, the system utilizes the knowledge graph(s). SAGE can be used by anyone for annotating Things and for their exploitation on the Web. The annotation of things is done through exact and partial matches. For the exact matches, the system makes explicit the name of the knowledge graphs it is sourced from. It also shows the type hierarchies for the matched named entities. The system is designed following the rule-based approach. In the current work, we describe the SAGE annotation system along with its features and various usage, and the experimental results.

This work is executed under the research project entitled "Integrated and Unified Data Model for Publication and Sharing of prolonged pandemic data as FAIR Semantic Data: COVID-19 as a case study", funded by the Indian Statistical Institute Kolkata.