Ontotext announced the realize of GraphDB 9.8, which offers text mining integration, notifications over Kafka, Helm charts, and performance improvements. The text mining plugin comes with out-of-the-box support for text analytic services such as Ontotext’s Tag API, GATE Cloud, and spaCy server, as well as an expressive mapping language, to register new services without coding. The extracted text annotations can be manipulated with SPARQL and either returned to the caller for further processing or stored directly into the repository where they will enrich the existing knowledge graph. This functionality covers a number of use-cases that rely on both RDF and text analytics.
The Kafka connector provides a means to synchronize changes to the RDF model to any downstream system via the Apache Kafka framework. Each Kafka connector instance will stay automatically up-to-date with the GraphDB repository data. The implementation is built on the same framework as the existing Elasticsearch, Solr and Lucene connectors and allows for precise mapping from RDF to JSON, such as defining fields based on property chains, nested document support as well as advanced filtering by type, literal language or a complex expression. GraphDB 9.8 comes with standard Helm charts and instructions that can help you get started with GraphDB Enterprise Edition on Kubernetes.