# The DL-Lite Family and Relations

arXiv: https://arxiv.org/abs/1401.3487 · HTML: https://mlsanity.com/paper/1401.3487/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jan 2014.

## Built on by (most cited first, 20 of 20)

- [Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases](https://mlsanity.com/paper/2303.14617/) (2023)
- [Shapley Value Computation in Ontology-Mediated Query Answering](https://mlsanity.com/paper/2407.20058/) (2024)
- [Frontiers and Exact Learning of ELI Queries under DL-Lite Ontologies](https://mlsanity.com/paper/2204.14172/) (2022)
- [PN-OWL: A Two Stage Algorithm to Learn Fuzzy Concept Inclusions from OWL Ontologies](https://mlsanity.com/paper/2303.07192/) (2023)
- [On the Power and Limitations of Examples for Description Logic Concepts](https://mlsanity.com/paper/2412.17345/) (2024)
- [Dealing with Inconsistency for Reasoning over Knowledge Graphs: A Survey](https://mlsanity.com/paper/2502.19023/) (2025)
- [On the Complexity of Learning Description Logic Ontologies](https://mlsanity.com/paper/2103.13694/) (2021)
- [Answering Fuzzy Queries over Fuzzy DL-Lite Ontologies](https://mlsanity.com/paper/2111.11779/) (2021)
- [A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases](https://mlsanity.com/paper/2303.07469/) (2023)
- [On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators(Extended Version)](https://mlsanity.com/paper/2501.13762/) (2025)
- [Extending Sticky-Datalog+/- via Finite-Position Selection Functions: Tractability, Algorithms, and Optimization](https://mlsanity.com/paper/2108.00903/) (2021)
- [QDEF and Its Approximations in OBDM](https://mlsanity.com/paper/2108.10021/) (2021)
- [SMT-Based Safety Verification of Data-Aware Processes under Ontologies (Extended Version)](https://mlsanity.com/paper/2108.12330/) (2021)
- [Conservative Extensions for Existential Rules](https://mlsanity.com/paper/2202.05689/) (2022)
- [Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology](https://mlsanity.com/paper/2306.07662/) (2023)
- [Automated planning with ontologies under coherence update semantics (Extended Version)](https://mlsanity.com/paper/2507.15120/) (2025)
- [Analysing Temporal Reasoning in Description Logics Using Formal Grammars](https://mlsanity.com/paper/2508.00575/) (2025)
- [LLM-based Argument Mining meets Argumentation and Description Logics: a Unified Framework for Reasoning about Debates](https://mlsanity.com/paper/2603.02858/) (2026)
- [How Hard is it to Decide if a Fact is Relevant to a Query?](https://mlsanity.com/paper/2604.22422/) (2026)
- [BoxLitE: A Faithful Knowledge Base Embedding Based on Convex Optimization](https://mlsanity.com/paper/2605.23937/) (2026)

## Abstract (arXiv)

The recently introduced series of description logics under the common moniker DL-Lite has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main aim of this article is to carry out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes: by (i) adding the Boolean connectives and (ii) number restrictions to concept constructs, (iii) allowing role hierarchies, (iv) allowing role disjointness, symmetry, asymmetry, reflexivity, irreflexivity and transitivity constraints, and (v) adopting or dropping the unique same assumption. We analyze the combined complexity of satisfiability for the resulting logics, as well as the data complexity of instance checking and answering positive existential queries. Our approach is based on embedding DL-Lite logics in suitable fragments of the one-variable first-order logic, which provides useful insights into their properties and, in particular, computational behavior.