@inproceedings{lin-zeldes-2021-wikigum,
    title = "{W}iki{GUM}: Exhaustive Entity Linking for Wikification in 12 Genres",
    author = "Lin, Jessica  and
      Zeldes, Amir",
    editor = "Bonial, Claire  and
      Xue, Nianwen",
    booktitle = "Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2021.law-1.18/",
    doi = "10.18653/v1/2021.law-1.18",
    pages = "170--175",
    abstract = "Previous work on Entity Linking has focused on resources targeting non-nested proper named entity mentions, often in data from Wikipedia, i.e. Wikification. In this paper, we present and evaluate WikiGUM, a fully wikified dataset, covering all mentions of named entities, including their non-named and pronominal mentions, as well as mentions nested within other mentions. The dataset covers a broad range of 12 written and spoken genres, most of which have not been included in Entity Linking efforts to date, leading to poor performance by a pretrained SOTA system in our evaluation. The availability of a variety of other annotations for the same data also enables further research on entities in context."
}