Survey on English Entity Linking on Wikidata

Tracking #: 2670-3884

This paper is currently under review
Authors: 
Cedric Moeller
Jens Lehmann
Ricardo Usbeck

Responsible editor: 
Guest Editors Advancements in Linguistics Linked Data 2021

Submission type: 
Survey Article
Abstract: 
Wikidata is an always up-to-date, community-driven, and multilingual knowledge graph. Hence, Wikidata is an attractive basis for Entity Linking, which is evident by the recent increase in published papers. This survey focuses on four subjects: (1) How do current Entity Linking approaches exploit the specific characteristics of Wikidata? (2) Which unexploited Wikidata characteristics are worth to consider for the Entity Linking task? (3) Which Wikidata Entity Linking datasets exist, how widely used are they and how are they constructed? (4) Do the characteristics of Wikidata matter for the design of Entity Linking datasets and if so, how? Our survey reveals that most Entity Linking approaches use Wikidata in the same way as any other knowledge graph missing the chance to leverage Wikidata-specific characteristics to increase quality. Almost all approaches employ specific properties like labels and sometimes descriptions but ignore characteristics like the hyper-relational structure. Thus, there is still room for improvement, for example, by including hyper-relational graph embeddings or type information. Many approaches also include information from Wikipedia which is easily combinable with Wikidata and provides valuable textual information which is Wikidata lacking. The current Wikidata-specific Entity Linking datasets do not differ in their annotation scheme from schemes for other knowledge graphs like DBpedia. The potential for multilingual and time-dependent datasets, naturally suited for Wikidata, is not lifted.
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Under Review