Generating a large-scale entity Linking dictionary from wikipedia link structure and article text

    Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

    5 Citations (Scopus)

    Abstract

    Wikipedia has been increasingly used as a knowledge base for open-domain Named Entity Linking and Disambiguation. In this task, a dictionary with entity surface forms plays an important role in finding a set of candidate entities for the mentions in text. Existing dictionaries mostly rely on the Wikipedia link structure, like anchor texts, redirect links and disambiguation links. In this paper, we introduce a dictionary for Entity Linking that includes name variations extracted from Wikipedia article text, in addition to name variations derived from the Wikipedia link structure. With this approach, we show an increase in the coverage of entities and their mentions in the dictionary in comparison to other Wikipedia based dictionaries.

    Original languageEnglish
    Title of host publicationProceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016
    EditorsNicoletta Calzolari, Khalid Choukri, Helene Mazo, Asuncion Moreno, Thierry Declerck, Sara Goggi, Marko Grobelnik, Jan Odijk, Stelios Piperidis, Bente Maegaard, Joseph Mariani
    PublisherEuropean Language Resources Association (ELRA)
    Pages2431-2434
    Number of pages4
    ISBN (Electronic)9782951740891
    Publication statusPublished - 2016
    Event10th International Conference on Language Resources and Evaluation, LREC 2016 - Portoroz, Slovenia
    Duration: 23 May 201628 May 2016

    Publication series

    NameProceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016

    Conference

    Conference10th International Conference on Language Resources and Evaluation, LREC 2016
    Country/TerritorySlovenia
    CityPortoroz
    Period23/05/1628/05/16

    Keywords

    • DBpedia
    • Entity linking
    • Name variation extraction
    • Wikipedia

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