WikiGUM: Exhaustive Entity Linking for Wikification in 12 Genres

EMNLP (LAW, DMR) 2021  ·  Jessica Lin, Amir Zeldes ·

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.

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Results from the Paper

Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Entity Linking GUM baseline F1 26.4 # 1


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