U-AIDA: a customizable system for named entity recognition, classification, and disambiguation

Recognizing and disambiguating entities such as people, organizations, events or places in natural language text are essential steps for many linguistic tasks such as information extraction and text categorization. A variety of named entity disambiguation methods have been proposed, but most of them focus on Wikipedia as a sole knowledge resource. This focus does not fit all application scenarios, and customization to the respective application domain is crucial. This dissertation addresses the problem of building an easily customizable system for named entity disambiguation. The first contribution is the development of a universal and flexible architecture that supports plugging in different knowledge resources. The second contribution is utilizing the flexible architecture to develop two domain-specific disambiguation systems. The third contribution is the design of a complete pipeline for building disambiguation systems for languages other than English that have poor annotated resources such as Arabic. The fourth contribution is a novel approach that performs fine-grained type classification of names in natural language text.

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