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Computer Science > Computation and Language

arXiv:2207.09562 (cs)
[Submitted on 19 Jul 2022]

Title:QuoteKG: A Multilingual Knowledge Graph of Quotes

Authors:Tin Kuculo, Simon Gottschalk, Elena Demidova
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Abstract: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.
Subjects: Computation and Language (cs.CL); Databases (cs.DB)
Cite as: arXiv:2207.09562 [cs.CL]
  (or arXiv:2207.09562v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2207.09562

Submission history

From: Tin Kuculo [view email]
[v1] Tue, 19 Jul 2022 21:32:59 UTC (974 KB)
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