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..
Revisiting Controlled Query Evaluation in Description Logics
Authors: Domenico Lembo, Riccardo Rosati, Domenico Fabio Savo
IJCAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study data complexity of this problem for ontologies specified in the Description Logics DL-Lite R and EL and for variants of the censor language... Some of the complexity results we provide are indeed obtained through mutual reduction between CQE and CQA. |
| Researcher Affiliation | Academia | Domenico Lembo1 , Riccardo Rosati1 and Domenico Fabio Savo2 1Sapienza Universit a di Roma 2Universit a degli Studi di Bergamo EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Algorithm CQ-Ent-DL-Lite R(E, q) and Algorithm 2: Algorithm CQk-Ent-EL (E, q) are provided. |
| Open Source Code | No | The paper does not contain any statements or links indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper is theoretical and focuses on description logics and query evaluation frameworks; it does not utilize datasets in the empirical sense common in machine learning or data analysis papers. Therefore, it does not provide information about publicly available training datasets. |
| Dataset Splits | No | The paper is theoretical and focuses on description logics and query evaluation frameworks; it does not utilize datasets in the empirical sense common in machine learning or data analysis papers. Therefore, it does not provide information about validation splits. |
| Hardware Specification | No | As a theoretical paper, it does not describe specific experimental setups or hardware used for computation. |
| Software Dependencies | No | As a theoretical paper, it describes algorithms and complexity, but does not specify any software dependencies with version numbers that would be required for empirical replication. |
| Experiment Setup | No | As a theoretical paper, it does not detail any experimental setup, hyperparameters, or system-level training settings. |