TARTAR - Transforming ARbitrary TAbles into fRames

Efficient automatic information handling has become increasingly important in information society. Most information on the Web is presented in the form of semi-structured or unstructured documents, encoded as a mixture of loosely structured natural language text and template units. The lack of metadata, which would precisely annotate the structure and semantics of documents, and ambiguity of natural language makes automatic computer processing very complex. The Semantic Web aims to overcome this bottleneck.

The contribution of this software package presents a novel method for automatic generation of knowledge models such as ontologies from arbitrary tabular structures found on the Web. The method is based on a grounded cognitive table model introduced by Hurst. The methodology is stepwise instantiated in four steps. In the first step, a table is transformed into regular matrix form. In the following two steps the table is handled from a structural and functional, and in the last step from a semantic point of view. The outcome of the method is threefold: a knowledge frame, an ontology, and a knowledge base, all encoded in an F-Logic representation language. A system is implemented in Java language, and consists of approximately 15.000 lines of code. In order to fully exploit (i.e. for query answering) the outcomes produced by the system, one can use an inference engine that supports F-Logic, like OntoBroker.