Tag: Knowledge graph
A knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts.
The Kairntech solution contains off-the-shelf models to extract entities from Wikidata, a well-know knowledge graph. These models speed up the document labeling process, and can be used to either pre-annotate or improve the quality of existing labels.
The linking of entities is a powerful way to improve overall quality.
How to use Wikidata to detect entities? – Kairntech Documentation
More on configuring Wikidata annotators – Kairntech Documentation
Examples to configure specific Wikidata annotators – Kairntech Documentation
Models are also created to extract relations between entities. These relation can then be used to enrich knowledge graphs. A good example is the Kairntech partnership with Fraunhofer SCAI.
Kairntech | Fraunhofer SCAI and Kairntech publish joint work about analysing scientific information
Fraunhofer SCAI and Kairntech succeed with AI-powered Relation Extraction for Indication-Specific Knowledge Graph assembly
A Knowledge Graph for psychiatric disorders SANKT AUGUSTIN. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI and the software company Kairntech (Grenoble) have created a knowledge graph for psychiatric disorders, especially psychoses. Knowledge graphs allow unstructured texts to be represented in a structured, comparable format. They visualize cause-and-effect models to help medical professionals
Bootstrap World Knowledge to extend Business Vocabulary and enhance Knowledge Graphs
Introduction Information extraction tends to target two situations: Extract entities from an existing vocabulary, or Create an extraction model from scratch when there is no existing vocabulary. However, sometimes the situation is a mixture of the two extremes: an incomplete business vocabulary exists but needs to be completed with relevant additional entities of the same