Epistemic Disjunctive Datalog for Querying Knowledge Bases

Authors: Gianluca Cima, Marco Console, Maurizio Lenzerini, Antonella Poggi

AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical First, we illustrate the syntax and the semantics of the novel query language. Second, we study the expressive power of different fragments of our new language and compare it with Disjunctive Datalog and its variants. Third, we outline the precise data complexity of answering queries in our new language over KBs expressed in various well-known formalisms.
Researcher Affiliation Academia Gianluca Cima, Marco Console, Maurizio Lenzerini, Antonella Poggi Sapienza University of Rome {cima, console, lenzerini, poggi}@diag.uniroma1.it
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No The paper describes theoretical work and does not mention the use of any datasets for training or evaluation, nor does it provide concrete access information for any dataset.
Dataset Splits No The paper is theoretical and does not discuss dataset splits for training, validation, or testing.
Hardware Specification No The paper is theoretical and does not mention any hardware specifications used for experiments.
Software Dependencies No The paper is theoretical and does not mention specific software dependencies with version numbers.
Experiment Setup No The paper describes theoretical work and does not detail any experimental setup, including hyperparameters or training configurations.