QuoteKG: A Multilingual Knowledge Graph of Quotes

Quotes of public figures can mark turning points in history. A quote can explain its originator’s actions, foreshadowing political or personal decisions and revealing character traits. Impactful quotes cross language barriers and influence the general population’s reaction to specific stances, always facing the risk of being misattributed or taken out of context. The provision of a cross-lingual knowledge graph of quotes that establishes the authenticity of quotes and their contexts is of great importance to allow the exploration of the lives of important people as well as topics from the perspective of what was actually said. In this paper, we present QuoteKG, the first multilingual knowledge graph of quotes. We propose the QuoteKG creation pipeline that extracts quotes from Wikiquote, a free and collaboratively created collection of quotes in many languages, and aligns different mentions of the same quote. QuoteKG includes nearly one million quotes in 55 languages, said by more than 69,000 people of public interest across a wide range of topics. QuoteKG is publicly available and can be accessed via a SPARQL endpoint.

  • Published in:
    European Semantic Web Conference
  • Type:
  • Authors:
    Kuculo, Tin; Gottschalk, Simon; Demidova, Elena
  • Year:

Citation information

Kuculo, Tin; Gottschalk, Simon; Demidova, Elena: QuoteKG: A Multilingual Knowledge Graph of Quotes, European Semantic Web Conference, 2022, https://arxiv.org/abs/2207.09562, Kuculo.etal.2022a,

Associated Lamarr Researchers

lamarr institute person demidova elena e1663924269458 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Elena Demidova

Principal Investigator Hybrid ML to the profile