Semantic Integration in Text

Semantic integration focuses on discovering, representing, and manipulating correspondences between entities in disparate data sources. The topic has been widely studied in the context of structured data, with problems being considered including ontology and schema matching, matching relational tuples, and reconciling inconsistent data values. In recent years, however, semantic integration over text has also received increasing attention. This article studies a key challenge in semantic integration over text: identifying whether different mentions of real-world entities, such as "JFK" and "John Kennedy," within and across natural language text documents, actually represent the same concept. We present a machine-learning study of this problem.