SemanticQA: Exploiting semantic associations for cross-document question answering

Abstract

As more data is being semantically annotated, it is getting more common that researchers in multiple disciplines rely on semantic repositories that contain large amounts of data in the form of ontologies as a compact source of information. One of the main issues currently facing these researchers is the lack of easy-to-use interfaces for data retrieval, due to the need to use special query languages or applications. In addition, the knowledge in these repositories might not be comprehensive or up-to-date due to several reasons, such as the discovery of new knowledge in the field after the repositories was created. In this paper, we introduce an enhanced version of our SemanticQA system that allows users to query semantic data repositories using natural language questions. If a user question cannot be answered solely from the ontology, SemanticQA detects the failing parts and attempts to answer these parts from web documents and plugs in the answers to answer the whole questions, which might involve a repetition of the same process if other parts fail.