RDF Knowledge Graph Visualization From a Knowledge Extraction System
This is an incremental tool for researchers or practitioners working with multilingual knowledge graphs to improve data exploration.
The paper presents a system for visualizing RDF knowledge graphs extracted from text using NLP and trigger detection, allowing users to filter subgraphs by ontology features and supporting multilingual interfaces in English, French, Arabic, and Chinese.
In this paper, we present a system to visualize RDF knowledge graphs. These graphs are obtained from a knowledge extraction system designed by GEOLSemantics. This extraction is performed using natural language processing and trigger detection. The user can visualize subgraphs by selecting some ontology features like concepts or individuals. The system is also multilingual, with the use of the annotated ontology in English, French, Arabic and Chinese.