Automatic Construction of Knowledge Graphs from Text and Structured Data: A Preliminary Literature Review

Authors Maraim Masoud , Bianca Pereira , John McCrae , Paul Buitelaar

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Maraim Masoud
  • Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, Ireland
Bianca Pereira
  • Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, Ireland
John McCrae
  • Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, Ireland
Paul Buitelaar
  • Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, Ireland

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Maraim Masoud, Bianca Pereira, John McCrae, and Paul Buitelaar. Automatic Construction of Knowledge Graphs from Text and Structured Data: A Preliminary Literature Review. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 19:1-19:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Knowledge graphs have been shown to be an important data structure for many applications, including chatbot development, data integration, and semantic search. In the enterprise domain, such graphs need to be constructed based on both structured (e.g. databases) and unstructured (e.g. textual) internal data sources; preferentially using automatic approaches due to the costs associated with manual construction of knowledge graphs. However, despite the growing body of research that leverages both structured and textual data sources in the context of automatic knowledge graph construction, the research community has centered on either one type of source or the other. In this paper, we conduct a preliminary literature review to investigate approaches that can be used for the integration of textual and structured data sources in the process of automatic knowledge graph construction. We highlight the solutions currently available for use within enterprises and point areas that would benefit from further research.

Subject Classification

ACM Subject Classification
  • Information systems → Information extraction
  • Knowledge Graph Construction
  • Enterprise Knowledge Graph


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