Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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.
Extended Property Paths: Writing More SPARQL Queries in a Succinct Way
Authors: Valeria Fionda, Giuseppe Pirrò, Mariano Consens
AAAI 2015 | Venue PDF | LLM Run Details | Input Tokens: 16,113 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,850 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We compare the two evaluation strategies on real data to highlight their pros and cons.We have implemented both a custom query processor for EPPs and the NREPPto SPARQL translation.Dataset and query set. We used a crawl of the FOAF social network ( 500MBs).Experiment 1: Running time. Fig. 6 shows the running times. |
| Researcher Affiliation | Academia | 1 De Ma CS, University of Calabria, Italy 2 We ST, University of Koblenz-Landau, Germany 3 MIE, University of Toronto, Canada |
| Pseudocode | Yes | Figure 3: EPPs evaluation algorithm. (Followed by detailed pseudocode blocks for EVALUATE, CLOSURE, BASE, and EVALTEST functions). |
| Open Source Code | Yes | We have implemented both a custom query processor for EPPs and the NREPPto SPARQL translation7. Available at http://extendedpps.wordpress.com |
| Open Datasets | Yes | Dataset and query set. We used a crawl of the FOAF social network ( 500MBs) obtained from the BTC20128 by traversing from the URI of T. Berners-Lee (TBL) foaf:knows predicates up to distance 4. 8http://km.aifb.kit.edu/projects/btc-2012 |
| Dataset Splits | No | The paper mentions using a dataset ('FOAF social network') but does not provide specific details about training, validation, or test splits (e.g., percentages, sample counts, or cross-validation setup). |
| Hardware Specification | Yes | The experiments have been performed on an Intel i5 machine with 8GBs RAM. |
| Software Dependencies | No | The paper mentions 'Jena ARQ' and its own custom implementations but does not specify any software names with version numbers for reproducibility. |
| Experiment Setup | No | The paper describes the dataset and query sets used, along with the average of 5 runs, but does not provide specific hyperparameter values or detailed system-level training configurations (e.g., learning rates, optimizer settings). |