Semi-automatic Knowledge Acquisition through CODA

In this paper, we illustrate the benefits deriving from the adoption of CODA (Computer-aided Ontology Development Architecture) for the semi-automatic acquisition of knowledge from unstructured information. Based on UIMA for the orchestration of analytics, CODA promotes the reuse of independently developed information extractors, while providing dedicated capabilities for projecting their output as RDF triples conforming to a user provided vocabulary. CODA introduces a clear workflow for the coordination of concurrently working teams through the incremental definition of a limited number of shared interfaces. In the proposed semi-automatic knowledge acquisition process, humans can validate the automatically produced triples, or refine them to increase their relevance to a specific domain model. An experimental user interface tries to raise efficiency and effectiveness of human involvement. For instance, candidate refinements are provided based on metadata about the triples to be refined, and the already assessed knowledge in the target semantic repository