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 [1].
Polynomial Datalog Rewritings for Expressive Description Logics with Closed Predicates
Authors: Shqiponja Ahmetaj, Magdalena Ortiz, Mantas Simkus
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We consider instance queries mediated by an ontology expressed in the expressive DL ALCHIO with closed predicates. We observe that such queries are non-monotonic and cannot be expressed in monotonic variants of DATALOG, but a polynomial time translation into disjunctive DATALOG extended with negation as failure is feasible. If no closed predicates are present in the case of classical instance checking in ALCHIO our translation yields a positive disjunctive DATALOG program of polynomial size. To the best of our knowledge, this is the ο¬rst polynomial time translation of an expressive (non-Horn) DL into disjunctive DATALOG. |
| Researcher Affiliation | Academia | Institute of Information Systems, TU Vienna, Austria |
| Pseudocode | Yes | Algorithm 1: Mark |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not perform empirical studies requiring datasets. |
| Dataset Splits | No | The paper is theoretical and does not perform empirical studies requiring dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not mention any hardware specifications for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |