Question Answering systems can be grouped into two categories: Simple, textual ones and hybrid QA systems. A textual QA system parses the input text with a POS tagger and tries to understand the grammar. It is influenced by Chomsky grammars and understands natural language like computer source-code. The assumption is, that all information are given by the text itself.
In contrast, hybrid QA systems combining textual data with linked data. Linked data is equal to a RDF database in the tripe storage format. The ontology in the background is used for enhancing textual information. Sometimes this concept is called “grounded Question answering system”. In the “QALD Challenge” many QA-systems were benchmarked against each other, and at least one paper describes the usage of YodaQA in the QALD challenge.
The QALD challenge is an ongoing benchmark contest founded 6 years ago and provides different tasks. Apart from the DBpedia and the biomedical dataset track, there is also a task available called “HOBBIT project” (Holistic Benchmarking of Big Linked Data) which is a question answering task for large scale applications.