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Shapes from Examples: Foundations of Shape Learning in Recursive SHACL

2026-08-06 12:02:36
Bente Gortworst, Cem Okulmus, Magdalena Ortiz, Anni-Yasmin Turhan
arXiv_AI
     
Abstract

SHACL shapes enable data graph validation, making automatic shape learning essential for knowledge graph applications. We investigate the well-known fitting approach to this task: given sets P and N of positive and negative example nodes from an input graph, compute a shape expression C, possibly using shape names defined in a recursive shape catalogue, that validates at every node in P and none in N. We focus on the case where C is written in a core fragment of SHACL corresponding to the Description Logic ELI. For the catalogue, we consider the well-founded, stable, and supported semantics. We address fitting existence and most specific fitting computation, establish tight exponential-time upper bounds for both problems, and obtain polynomial bounds for relevant special cases.

Abstract (translated)

URL

https://arxiv.org/abs/2607.27934

PDF

https://arxiv.org/pdf/2607.27934.pdf

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