QUASAR: querying annotation, structure, and reasoning

An increasing number of systems provide the ability to semantically annotate documents. OpenCalais [4], Evri API [2], Zemanta [6], and Alchemy API [1] are web-hosted systems that return annotated documents, i. e. documents with annotations that are overlayed on the document structure. Many of the annotations can be linked to standard ontologies, such as DBpedia and YAGO. These annotations give insight as to the meaning of documents in a variety of ways, identifying entities and relationships inside them, classifying them according to topic or theme, and giving the attitude or sentiment of a document or document fragment. In order for users (or applications) to make use of these annotations with a means to access and manipulate documents that contain them, we provide a query language for doing this and demonstrate its utility on a demo system built on top of diverse semantic annotators and external ontologies. We explain how integrating semantic annotations and utilizing external knowledge helps in increasing the quality of query answers over annotated documents by both filtering out irrelevant answers and obtaining extra answers that are not explicitly available in the annotated documents.