LILLIE: Information extraction and database integration using linguistics and learning-based algorithms

Querying both structured and unstructured data via a single common query interface such as SQL or natural language has been a long standing research goal. Moreover, as methods for extracting information from unstructured data become ever more powerful, the desire to integrate the output of such extraction processes with “clean”, structured data grows. We are convinced that for successful integration into databases, such extracted information in the form of “triples” needs to be both (1) of high quality and (2) have the necessary generality to link up with varying forms of structured data. It is the combination of both these aspects, which heretofore have been usually treated in isolation, where our approach breaks new ground.