Resources and Evaluations for Danish Entity Resolution

Maria Jung Barrett, Hieu Lam, Martin Wu, Ophélie Lacroix, Barbara Plank, Anders Søgaard

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Automatic coreference resolution is understudied in Danish even though most of the Danish Dependency Treebank (Buch-Kromann, 2003) is annotated with coreference relations. This paper describes a conversion of its partial, yet well-documented, coreference relations into coreference clusters and the training and evaluation of coreference models on this data. To the best of our knowledge, these are the first publicly available, neural coreference models for Danish. We also present a new entity linking annotation on the dataset using WikiData identifiers, a named entity disambiguation (NED) dataset, and a larger automatically created NED dataset enabling wikily supervised NED models. The entity linking annotation is benchmarked using a state-of-the-art neural entity disambiguation model.
Original languageEnglish
Title of host publicationFourth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)
PublisherAssociation for Computational Linguistics
Publication date2021
Pages63–69
Publication statusPublished - 2021

Keywords

  • Coreference resolution
  • Danish language processing
  • Dependency Treebank
  • Neural models
  • Entity linking
  • WikiData
  • Named entity disambiguation (NED)
  • Wikily supervised models
  • Coreference clusters
  • Natural language processing (NLP)

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