Abstract and Keywords
Information extraction constructs a structured knowledge representation from unstructured text, so that the knowledge may be further used for search, inference, and analysis. Given a specification of select types of entities, semantic relations, and events, it builds a database from instances of this information in text. This chapter describes the stages of processing involved and considers how such systems may be built using hand-coded rules, supervised training, and semi-supervised training.
Keywords: information extraction, knowledge representation, named entity identification, semantic relation identification, event identification, supervised training, semi-supervised training, bootstrapping
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