A Method of Recognizing Entity and Relation

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Author(s): Xinghua Fan (Chongqing University of Posts and Telecommunications, China)
Copyright: 2009
Pages: 8
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch189

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Abstract

Entity and relation recognition, i.e. assigning semantic classes (e.g., person, organization and location) to entities in a given sentence and determining the relations (e.g., born-in and employee-of) that hold between the corresponding entities, is an important task in areas such as information extraction (IE) (Califf and Mooney, 1999; Chinchor, 1998; Freitag, 2000; Roth and Yih, 2001), question answering (QA) (Voorhees, 2000; Changki Lee et al., 2007) and story comprehension (Hirschman et al., 1999). In a QA system, many questions ask for the specific entities involved in some relations. For example, the question that “Where was Poe born?” in TREC-9 asks for the location entity in which Poe was born. In a typical IE extraction task such as constructing a jobs database from unstructured text, the system has to extract many meaning entities like title and salary, ideally, to determine whether the entities are associated with the same position.

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