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].
Capturing Relational Schemas and Functional Dependencies in RDFS
Authors: Diego Calvanese, Wolfgang Fischl, Reinhard Pichler, Emanuel Sallinger, Mantas Simkus
AAAI 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We thus introduce expressive identification constraints to capture functional dependencies and define an RDF Normal Form, which precisely captures the classical Boyce-Codd Normal Form of relational schemas. and We now show that RNF captures BCNF in RGs using the relational to RDF graph direct mapping. Theorem 4. Let R be a relation symbol and Σ a set of fds over R. Then (R, Σ) is in BCNF iff rdm(R, Σ) is in RNF. and Algorithm 1: CHECKRNF... Theorem 5. The algorithm CHECKRNF in Algorithm 1 is a decision procedure for RNF. Theorem 6. Deciding whether T is in RNF is feasible in polynomial time. |
| Researcher Affiliation | Academia | Diego Calvanese KRDB Research Centre Free Univ. of Bozen-Bolzano, Italy EMAIL Wolfgang Fischl, Reinhard Pichler, Emanuel Sallinger, Mantas ˇSimkus Institute of Information Systems Vienna Univ. of Technology, Austria EMAIL |
| Pseudocode | Yes | Algorithm 1: CHECKRNF |
| Open Source Code | No | The paper does not mention releasing open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not use or provide information about publicly available datasets for experimental evaluation. |
| Dataset Splits | No | The paper does not provide specific dataset split information (training, validation, test) as it is a theoretical work. |
| Hardware Specification | No | The paper is theoretical and does not provide specific hardware details for running experiments. |
| Software Dependencies | No | The paper is theoretical and does not provide specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not provide specific experimental setup details, hyperparameters, or training configurations. |