relation: http://eprints.imtlucca.it/1889/ title: Dexter: an open source framework for entity linking creator: Ceccarelli, Diego creator: Lucchese, Claudio creator: Perego, Raffaele creator: Orlando, Salvatore creator: Trani, Salvatore subject: QA75 Electronic computers. Computer science subject: QA76 Computer software description: We introduce Dexter, an open source framework for entity linking. The entity linking task aims at identifying all the small text fragments in a document referring to an entity contained in a given knowledge base, e.g., Wikipedia. The annotation is usually organized in three tasks. Given an input document the first task consists in discovering the fragments that could refer to an entity. Since a mention could refer to multiple entities, it is necessary to perform a disambiguation step, where the correct entity is selected among the candidates. Finally, discovered entities are ranked by some measure of relevance. Many entity linking algorithms have been proposed, but unfortunately only a few authors have released the source code or some APIs. As a result, evaluating today the performance of a method on a single subtask, or comparing different techniques is difficult. In this work we present a new open framework, called Dexter, which implements some popular algorithms and provides all the tools needed to develop any entity linking technique. We believe that a shared framework is fundamental to perform fair comparisons and improve the state of the art. publisher: ACM date: 2013-10-28 type: Book Section type: PeerReviewed format: application/pdf language: en identifier: http://eprints.imtlucca.it/1889/1/paper.pdf identifier: Ceccarelli, Diego and Lucchese, Claudio and Perego, Raffaele and Orlando, Salvatore and Trani, Salvatore Dexter: an open source framework for entity linking. In: ESAIR '13 Proceedings of the sixth international workshop on Exploiting semantic annotations in information retrieval. ACM, pp. 17-20. ISBN 978-1-4503-2413-7 (2013) relation: http://dl.acm.org/citation.cfm?id=2513212