English

Commonsense Knowledge in Wikidata

Artificial Intelligence 2020-10-19 v2

Abstract

Wikidata and Wikipedia have been proven useful for reason-ing in natural language applications, like question answering or entitylinking. Yet, no existing work has studied the potential of Wikidata for commonsense reasoning. This paper investigates whether Wikidata con-tains commonsense knowledge which is complementary to existing commonsense sources. Starting from a definition of common sense, we devise three guiding principles, and apply them to generate a commonsense subgraph of Wikidata (Wikidata-CS). Within our approach, we map the relations of Wikidata to ConceptNet, which we also leverage to integrate Wikidata-CS into an existing consolidated commonsense graph. Our experiments reveal that: 1) albeit Wikidata-CS represents a small portion of Wikidata, it is an indicator that Wikidata contains relevant commonsense knowledge, which can be mapped to 15 ConceptNet relations; 2) the overlap between Wikidata-CS and other commonsense sources is low, motivating the value of knowledge integration; 3) Wikidata-CS has been evolving over time at a slightly slower rate compared to the overall Wikidata, indicating a possible lack of focus on commonsense knowledge. Based on these findings, we propose three recommended actions to improve the coverage and quality of Wikidata-CS further.

Keywords

Cite

@article{arxiv.2008.08114,
  title  = {Commonsense Knowledge in Wikidata},
  author = {Filip Ilievski and Pedro Szekely and Daniel Schwabe},
  journal= {arXiv preprint arXiv:2008.08114},
  year   = {2020}
}

Comments

WikiData Workshop at ISWC 2020

R2 v1 2026-06-23T17:56:50.775Z