Cross-Document Entity Tracking

Abstract

The main focus of current work is to analyze useful features for linking and disambiguating person entities across documents. The more general problem of linking and disambiguating any kind of entity is known as entity detection and tracking (EDT) or noun phrase coreference resolution. EDT has applications in many important areas of information retrieval: clustering results in search engines when looking for a particular person; possibility to answer questions such as “Who was Woodward’s source in the Plame scandal?” with “senior administration official” or “Richard Armitage” and information fusion from multiple documents. In current work person entities are limited to names and nominal entities. We emphasize the linguistic aspect of cross-document EDT: testing novel features useful in EDT across documents, such as the syntactic and semantic characteristics of the entities. The most important class of new features are contextual features, at varying levels of detail: events, related named-entities, and local context. The validity of the features is evaluated on a corpus annotated for cross-document coreference resolution of person names and nominals, and also on a corpus annotated only for names.