Chasing Sets: How to Use Existential Rules for Expressive Reasoning
Authors: David Carral, Irina Dragoste, Markus Krötzsch, Christian Lewe
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We introduce Datalog(S) Datalog with support for sets as a surface language for such translations, and show that it can be captured in a decidable fragment of existential rules. We then implement several known inference methods in Datalog(S), and empirically show that an existing existential rule reasoner can thus be used to solve practical reasoning problems. |
| Researcher Affiliation | Academia | David Carral , Irina Dragoste , Markus Kr otzsch and Christian Lewe Knowledge-Based Systems Group, TU Dresden, Dresden, Germany {david.carral, irina.dragoste, markus.kroetzsch, christian.lewe}@tu-dresden.de |
| Pseudocode | No | The paper presents rule sets in figures (e.g., Figures 1 and 2) but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | Details we had to omit are found online [Carral et al., 2019]. |
| Open Datasets | Yes | We classified five large and diverse ontologies from the Oxford Ontology Repository:3 00040 (GO x-anatomy), 00048 (GO x-taxon), 00477 (Gazetteer), 00533 (Ch EBI mol. function), and 00786 (NCI). The ontology statistics and results are shown in Figure 3. We used several benchmark datasets that Zhou et al. [2015] created by sampling data for two large ontologies: the real-world knowledge base Reactome, and the synthetic benchmark UOBM. |
| Dataset Splits | No | The paper uses established ontologies and benchmark datasets for classification and retrieval tasks but does not specify training, validation, or test splits or cross-validation methodology. |
| Hardware Specification | Yes | All experiments where run on a Mac Book Pro (2.4GHz Intel Core i5, 8GB RAM). |
| Software Dependencies | No | The paper mentions using 'VLog' and 'Konclude' but does not specify their version numbers or other software dependencies with versions. |
| Experiment Setup | No | The paper describes the logical rules and their translation, but it does not provide specific experimental setup details such as hyperparameters, learning rates, batch sizes, or optimizer settings. |