[2508.13663] Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints

Computer Science > Artificial Intelligence arXiv:2508.13663 (cs) [Submitted on 19 Aug 2025 (v1), last revised 26 Mar 2026 (this version, v4)] Title:Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints Authors:Daniel Daza, Alberto Bernardi, Luca Costabello, Christophe Gueret, Masoud Mansoury, Michael Cochez, Martijn Schut View a PDF of the paper titled Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints, by Daniel Daza and 6 other authors View PDF HTML (experimental) Abstract:Methods for query answering over incomplete knowledge graphs retrieve entities that are \emph{likely} to be answers, which is particularly useful when such answers cannot be reached by direct graph traversal due to missing edges. However, existing approaches have focused on queries formalized using first-order-logic. In practice, many real-world queries involve constraints that are inherently vague or context-dependent, such as preferences for attributes or related categories. Addressing this gap, we introduce the problem of query answering with soft constraints. We formalize the problem and introduce two efficient methods designed to adjust query answer scores by incorporating soft constraints without disrupting the original answers to a query. These methods are lightweight, requiring tuning only two parameters or a small neural network trained to capture soft constraints while maintaining the original ranking structure. To evaluate the task, we extend ...