Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Ontology-Mediated Queries with Closed Predicates
Authors: Carsten Lutz, Inanc Seylan, Frank Wolter
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In particular, we contribute to the classification of the data complexity of such queries in several relevant DLs. The complexity of an OMQC Q = (T , ΣA, ΣC, q) is the complexity to decide, given a ΣA-ABox A, whether T , A |=c(ΣC) q. |
| Researcher Affiliation | Academia | 1University of Bremen 2University of Liverpool, UK |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements about releasing source code or links to a code repository for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not use or reference any datasets for empirical evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe any software dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |