mlsanityData to 7 Oct 2026

Construction of Knowledge Graphs: State and Challenges

arXiv 2302.11509 ↗First posted 22 Feb 2023cs.AI cs.DB cs.LGcited by 12

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Abstract (arXiv)

With knowledge graphs (KGs) at the center of numerous applications such as recommender systems and question answering, the need for generalized pipelines to construct and continuously update such KGs is increasing. While the individual steps that are necessary to create KGs from unstructured (e.g. text) and structured data sources (e.g. databases) are mostly well-researched for their one-shot execution, their adoption for incremental KG updates and the interplay of the individual steps have hardly been investigated in a systematic manner so far. In this work, we first discuss the main graph models for KGs and introduce the major requirement for future KG construction pipelines. Next, we provide an overview of the necessary steps to build high-quality KGs, including cross-cutting topics such as metadata management, ontology development, and quality assurance. We then evaluate the state of the art of KG construction w.r.t the introduced requirements for specific popular KGs as well as some recent tools and strategies for KG construction. Finally, we identify areas in need of further research and improvement.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 76 of its 378 references that are in the map. First posted on arXiv 22 Feb 2023.

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76 of 378 references.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 6; 2026: 2.

12 papers.