mlsanityData to 13 Oct 2026

WikiGUM: Exhaustive Entity Linking for Wikification in 12 Genres

arXiv 2109.07449 ↗First posted 15 Sep 2021cs.CLcited by 9

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Abstract (arXiv)

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.

Key facts. Cited by 9 papers in the map (data through 13 Oct 2026). Builds on 4 of its 23 references that are in the map. First posted on arXiv 15 Sep 2021.

Builds on

4 of 23 references.

References · 4

  1. 2018End-to-End Neural Entity Linkingcited by 85
  2. 2019NNE: A Dataset for Nested Named Entity Recognition in English Newswirecited by 25
  3. 2014Analysis of Named Entity Recognition and Linking for Tweetscited by 20
  4. 2019Fast End-to-End Wikificationcited by 3

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 2; 2025: 3; 2026: 1.

9 papers.