Populating Narratives Using Wikidata Events: An Initial Experiment

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 988)


The study presented in this paper is part of our research aimed at improving the search functionalities of current Digital Libraries using formal narratives. Narratives are intended as sequences of events. We present the results of an initial experiment to detect and extract implicit events from the Wikidata knowledge base in order to construct a narrative in a semi-automatic way. Wikidata contains many historical entities, but comparably few events. The reason is that most events in Wikidata are represented in an implicit way, e.g. by listing a date of birth instead of having an event of type “birth”. For this reason, we decided to generate what we call the Wikidata Event Graph (WEG), i.e. the graph of implicit events found in Wikidata. We performed an initial experiment taking as case study the narrative of the life of Italian poet Dante Alighieri. Only one event of the life of Dante is explicitly represented in Wikidata as instance of the class Q1190554 Occurrence. Using the WEG, we were able to automatically detect 31 more events of Dante’s life that were present in Wikidata in an implicit way.


Wikidata Narratives Semantic Web Ontology Digital Libraries 


  1. 1.
    Bartalesi, V.: An ontology for narratives. Ph.D. thesis, University of Pisa (2017)Google Scholar
  2. 2.
    Bartalesi, V., Meghini, C., Metilli, D.: A conceptualisation of narratives and its expression in the CRM. Int. J. Metadata Semant. Ontol. 12(1), 35–46 (2017)CrossRefGoogle Scholar
  3. 3.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data: the story so far. In: Sheth, A. (ed.) Semantic Services, Interoperability and Web Applications: Emerging Concepts, pp. 205–227. IGI Global, Hershey (2011)CrossRefGoogle Scholar
  4. 4.
    Doerr, M.: The CIDOC Conceptual Reference Module: an ontological approach to semantic interoperability of metadata. AI Mag. 24(3), 75 (2003)Google Scholar
  5. 5.
    Erxleben, F., Günther, M., Krötzsch, M., Mendez, J., Vrandečić, D.: Introducing Wikidata to the linked data web. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 50–65. Springer, Cham (2014). Scholar
  6. 6.
    Färber, M., Bartscherer, F., Menne, C., Rettinger, A.: Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Semant. Web 9(1), 1–53 (2017)CrossRefGoogle Scholar
  7. 7.
    Lehmann, J., et al.: DBpedia–a large-scale, multilingual knowledge base extracted from wikipedia. Semant. Web 6(2), 167–195 (2015)Google Scholar
  8. 8.
    Shen, W., Wang, J., Han, J.: Entity linking with a knowledge base: issues, techniques, and solutions. IEEE Trans. Knowl. Data Eng. 27(2), 443–460 (2015)CrossRefGoogle Scholar
  9. 9.
    Suchanek, F.M., Kasneci, G., Weikum, G.: YAGO: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, pp. 697–706. ACM (2007)Google Scholar
  10. 10.
    Vrandečić, D., Krötzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78–85 (2014)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” – CNRPisaItaly

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