Bounded Descriptions for Knowledge Graph Traversal by Language Models
Henselmann D, Harth A (2026)
Publication Type: Conference contribution
Publication year: 2026
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 16549 LNCS
Pages Range: 379-397
Conference Proceedings Title: Lecture Notes in Computer Science
Event location: Dubrovnik, HRV
ISBN: 9783032251558
DOI: 10.1007/978-3-032-25156-5_20
Abstract
A bounded description of a resource is a useful default subgraph that represents relevant information. When accessing RDF knowledge graphs, bounded descriptions are returned for SPARQL DESCRIBE queries or for HTTP GET requests on Linked Data. Concise Bounded Description (CBD) is the de facto default, but only provides conditional reachability of connected resources, limiting its usefulness for knowledge graph traversal. This paper outlines alternative bounded description specifications consisting of chained and parallel combinations of construction steps. Furthermore, characteristics of bounded description specifications are introduced, including ontology awareness, applicability, and reachability. The evaluation challenges the traversal of a knowledge graph with n-ary relations using retrieved bounded descriptions. Results confirm limitations of the CBD specification, highlight the impact of reachability, and bring attention to ontology-aware and set-specific bounded descriptions.
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Germany (DE)How to cite
APA:
Henselmann, D., & Harth, A. (2026). Bounded Descriptions for Knowledge Graph Traversal by Language Models. In Maribel Acosta, Marieke van Erp, Sebastian Rudolph, Olaf Hartig, Blerina Spahiu, Anisa Rula, Daniel Garijo, Francesco Osborne (Eds.), Lecture Notes in Computer Science (pp. 379-397). Dubrovnik, HRV: Springer Science and Business Media Deutschland GmbH.
MLA:
Henselmann, Daniel, and Andreas Harth. "Bounded Descriptions for Knowledge Graph Traversal by Language Models." Proceedings of the 23rd European Semantic Web Conference, ESWC 2026, Dubrovnik, HRV Ed. Maribel Acosta, Marieke van Erp, Sebastian Rudolph, Olaf Hartig, Blerina Spahiu, Anisa Rula, Daniel Garijo, Francesco Osborne, Springer Science and Business Media Deutschland GmbH, 2026. 379-397.
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