2026-10-01T22:37:51Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:28087 2026-09-30T14:08:58Z ddc:004 open_access

AutoRML: Automated Declarative RDF Generation Leveraging Semantic Table Annotation Dasoulas, Ioannis Elhalawati, Ali Dimou, Anastasia Knowledge Graphs Mapping Languages RML Semantic Table Annotation Entity Linking Property Linking Knowledge graph (KG) construction from heterogeneous data is a complex process that requires good understanding of the data to semantically annotate entities and their relations, and define the terms of the KG based on these entities and relations. Due to this complexity, KG construction remains primarily manual. On the one hand, semantic annotation systems focus on entity and relation disambiguation, but ultimately they do not construct a KG. On the other hand, declarative systems which typically construct the KGs, assume that the semantic annotations are already available. However, the two types of systems have not yet been effectively integrated. In this paper, we propose a formal method that integrates semantic annotation and declarative systems for automating end-to-end KG construction through automated declarative mappings generation. We validate our approach by creating AutoRML, a system that can leverage different semantic annotation frameworks to annotate tabular data and declaratively construct KGs. Evaluations demonstrate that AutoRML can construct KGs identical to manually constructed ones when the same target knowledge base is used as reference. AutoRML supports semi-automatic KG construction when semantic annotations are insufficient for full automation, generating human-friendly declarative mappings that can be refined by experts. We showcase AutoRML’s performance with diverse datasets, showing its potential in automating data integration workflows. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ioannis Dasoulas and Ali Elhalawati and Anastasia Dimou 2026 Is Part Of TGDK, Volume 4, Issue 3 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 3 Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/TGDK.4.3.2 urn:nbn:de:0030-drops-280874 https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.3.2 eng https://creativecommons.org/licenses/by/4.0/legalcode