# Provenance-Enhanced Statements in Knowledge Graphs

arXiv: https://arxiv.org/abs/2606.15246 · HTML: https://mlsanity.com/paper/2606.15246/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 55 references that are in the map.
- First posted on arXiv 13 Jun 2026.

## Builds on (most cited first, 8 of 8)

- [Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications](https://mlsanity.com/paper/1305.3506/) (2013)
- [Broadening the Scope of Nanopublications](https://mlsanity.com/paper/1303.2446/) (2013)
- [Semantic Units: Organizing knowledge graphs into semantically meaningful units of representation](https://mlsanity.com/paper/2301.01227/) (2023)
- [Easy and complex: new perspectives for metadata modeling using RDF-star and Named Graphs](https://mlsanity.com/paper/2211.16195/) (2022)
- [Query Answering over Contextualized RDF/OWL Knowledge with Forall-Existential Bridge Rules: Decidable Finite Extension Classes (Post Print)](https://mlsanity.com/paper/1512.03899/) (2015)
- [Logical Inferences with Contexts of RDF Triples](https://mlsanity.com/paper/1701.05724/) (2017)
- [eSPARQL: Representing and Reconciling Agnostic and Atheistic Beliefs in RDF-star Knowledge Graphs](https://mlsanity.com/paper/2407.21483/) (2024)
- [From Knowledge to Conjectures: A Modal Framework for Reasoning about Hypotheses](https://mlsanity.com/paper/2508.07304/) (2025)

## Abstract (arXiv)

Provenance-enhanced statements of the form "according to X, varphi" are pervasive in contemporary knowledge graphs, especially in domains where graph content primarily represents claims, interpretations, and hypotheses (capta) rather than observer-independent facts (data). Current provenance models can record who asserted what, but they typically treat provenance as semantically neutral, leaving underspecified how attributed claims relate to factual commitment, to one another, and to reasoning. In this paper we introduce DEC, a framework that interprets provenance predicates as indicators of epistemic stance and groups provenance-homogeneous sets of statements into cognitive worlds. Drawing on cognitive modal logics (doxastic, epistemic, and conjectural), DEC characterizes locality, rationality, and controlled permeation between cognitive worlds and a distinguished factual core ("reality"), thereby enabling principled reasoning over attributed content without collapsing disagreements into inconsistencies. We formalize a DEC interpretation for RDF datasets that is conservative over RDF~1.2 semantics, clarify the role of intensionality and identity (including the Superman paradox), and illustrate the approach on common Semantic Web representations (named graphs, quoted triples/RDF-star, and reification). Finally, we describe our prototype DEC reasoner implemented as a Fuseki dataset module, supporting controlled factualisation and explicit detection of disagreements and delusions.