On the Expressivity of ASK Queries in SPARQL

Authors: Xiaowang Zhang, Jan Van den Bussche, Kewen Wang, Heng Zhang, Xuanxing Yang, Zhiyong Feng3057-3064

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Reproducibility Variable Result LLM Response
Research Type Theoretical This paper is a first systematic study of the relative expressive power of various fragments of ASK queries in SPARQL.
Researcher Affiliation Academia 1College of Intelligence and Computing, Tianjin University, Tianjin, China 2Faculty of Sciences, Hasselt University, Hasselt, Belgium 3School of Information and Communication Technology, Griffith University, Brisbane, Australia 4Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China
Pseudocode No The paper does not contain any sections explicitly labeled as 'Pseudocode' or 'Algorithm', nor are there structured algorithm blocks.
Open Source Code No The paper does not provide any information about the availability of open-source code for the described methodology.
Open Datasets No This paper is theoretical and does not involve the use of datasets for training or evaluation.
Dataset Splits No This paper is theoretical and does not involve the use of datasets, thus no validation split information is provided.
Hardware Specification No The paper is theoretical and does not describe computational experiments that would require specific hardware specifications.
Software Dependencies No The paper is theoretical and does not mention specific software dependencies with version numbers required for replication.
Experiment Setup No The paper is theoretical and does not involve empirical experiments, therefore no experimental setup details like hyperparameters are provided.