The combined approach to query answering in DL-Lite
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Databases and related information systems can benefit \nfrom the use of ontologies to enrich the data with \ngeneral background knowledge. The DL-Lite family \nof ontology languages was specifically tailored towards \nsuch ontology-based data access, enabling an implementation \nin a relational database management system \n(RDBMS) based on a query rewriting approach. In \nthis paper, we propose an alternative approach to implementing \nontology-based data access in DL-Lite. The \ndistinguishing feature of our approach is to allow rewriting \nof both the query and the data. We show that, in contrast \nto the existing approaches, no exponential blowup \nis produced by the rewritings. Based on experiments \nwith a number of real-world ontologies, we demonstrate \nthat query execution in the proposed approach is often \nmore efficient than in existing approaches, especially \nfor large ontologies. We also show how to seamlessly \nintegrate the data rewriting step of our approach into \nan RDBMS using views (which solves the update problem) \nand make an interesting observation regarding the \nsuccinctness of queries in the original query rewriting \napproach.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it