A Rule-Based Approach to Specifying Preferences over Conflicting Facts and Querying Inconsistent Knowledge Bases

2025-08-11

AI Summary

This work addresses the challenge of modeling priority among conflicting facts in inconsistent knowledge bases. We propose a rule-based declarative framework: first, preference rules are formally defined to express prioritization relationships among facts; second, we establish a decidable acyclicity condition for priority relations and design multiple cycle-elimination strategies to ensure both rationality and explainability of the priority structure; third, we implement preference resolution, cycle elimination, and repair semantics integration within Answer Set Programming (ASP), yielding an end-to-end priority-aware query system. Experimental evaluation demonstrates that our approach efficiently handles complex, dynamic preference rules, producing semantically consistent and verifiable query answers. It significantly enhances trustworthy reasoning over inconsistent knowledge bases.

Technology Category

• Knowledge Representation and Reasoning: Preferences
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Repair-based semantics have been extensively studied as a means of obtaining meaningful answers to queries posed over inconsistent knowledge bases (KBs). While several works have considered how to exploit a priority relation between facts to select optimal repairs, the question of how to specify such preferences remains largely unaddressed. This motivates us to introduce a declarative rule-based framework for specifying and computing a priority relation between conflicting facts. As the expressed preferences may contain undesirable cycles, we consider the problem of determining when a set of preference rules always yields an acyclic relation, and we also explore a pragmatic approach that extracts an acyclic relation by applying various cycle removal techniques. Towards an end-to-end system for querying inconsistent KBs, we present a preliminary implementation and experimental evaluation of the framework, which employs answer set programming to evaluate the preference rules, apply the desired cycle resolution techniques to obtain a priority relation, and answer queries under prioritized-repair semantics.

Problem

• Specifying preferences over conflicting facts in inconsistent KBs
• Determining acyclic relations from preference rules
• Querying inconsistent KBs using prioritized-repair semantics

Innovation

• Rule-based framework for fact preferences
• Cycle removal in preference relations
• Answer set programming for query resolution