Pith. sign in

REVIEW 1 cited by

The KG-ER Conceptual Schema Language

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2508.02548 v3 pith:7DKWGJAI submitted 2025-08-04 cs.DB cs.AI

The KG-ER Conceptual Schema Language

Enrico Franconi , Beno\^it Groz , Jan Hidders , Nina Pardal , S{\l}awek Staworko , Jan Van den Bussche , Piotr Wieczorek This is my paper
classification cs.DB cs.AI
keywords graphsknowledgeconceptualkg-erlanguageschemacapturedatabases
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

We propose KG-ER, a conceptual schema language for knowledge graphs that describes the structure of knowledge graphs independently of their representation (relational databases, property graphs, RDF) while helping to capture the semantics of the information stored in a knowledge graph.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. More with Less -- Bethel Allocation and Precision-Preserving Sample Size Reduction via Hierarchical Bayes Modelling

    stat.ME 2026-03 unverdicted novelty 5.0

    Combining Bethel multivariate allocation with Hierarchical Bayes small-area modelling can meet multi-variable, multi-domain CV targets with a smaller sample than ad-hoc Neyman-max designs.