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].
Ontology-Mediated Query Answering for Key-Value Stores
Authors: Meghyn Bienvenu, Pierre Bourhis, Marie-Laure Mugnier, Sophie Tison, Federico Ulliana
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a novel rule-based ontology language for JSON records and investigate its computational properties. By establishing an interesting and nontrivial connection to word rewriting, we are able to pinpoint the exact combined complexity of query answering in our framework and obtain tractability results for data complexity. |
| Researcher Affiliation | Academia | CNRS, France Universit e de Montpellier, France Universit e de Lille 1, France INRIA, France {๏ฌrstname.lastname}@inria.fr |
| Pseudocode | No | The paper describes theoretical concepts and proofs, but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement about releasing open-source code or a link to a code repository for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not describe using any datasets for empirical evaluation. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments or dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any software implementations or dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |