Named Entity Extraction and Disambiguation from an Uncertainty Perspective

M. B. Habib, M. van Keulen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademic

    Abstract

    Named entity extraction and disambiguation have received much attention in recent years. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web. This work addresses two problems with named entity extraction and disambiguation. First, almost no existing works examine the extraction and disambiguation interdependency. Second, existing disambiguation techniques mostly take as input extracted named entities without considering the uncertainty and imperfection of the extraction process. It is the aim of this work to investigate both avenues and to show that explicit handling of the uncertainty of annotation has much potential for making both extraction and disambiguation more robust. We conducted experiments with a set of holiday home descriptions with the aim to extract and disambiguate toponyms as a representative example of named entities. We show that the effectiveness of extraction influences the effectiveness of disambiguation, and reciprocally, how retraining the extraction models with information automatically derived from the disambiguation results, improves the extraction models. This mutual reinforcement is shown to even have an effect after several iterations.
    Original languageEnglish
    Title of host publicationProceedings of the Dutch Belgian Database Day, DBDBD 2011, University of Twente, The Netherlands
    Place of PublicationEnschede
    PublisherCentre for Telematics and Information Technology, University of Twente
    Pages12
    Number of pages1
    Publication statusPublished - 1 Dec 2011

    Keywords

    • Named Entity Recognition Named Entity Linking Named Entity Extraction Named Entity Disambiguation

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