Expressive Completeness of Existential Rule Languages for Ontology-based\n Query Answering
Bibliographic record
Abstract
Existential rules, also known as data dependencies in Databases, have been\nrecently rediscovered as a promising family of languages for Ontology-based\nQuery Answering. In this paper, we prove that disjunctive embedded dependencies\nexactly capture the class of recursively enumerable ontologies in\nOntology-based Conjunctive Query Answering (OCQA). Our expressive completeness\nresult does not rely on any built-in linear order on the database. To establish\nthe expressive completeness, we introduce a novel semantic definition for OCQA\nontologies. We also show that neither the class of disjunctive tuple-generating\ndependencies nor the class of embedded dependencies is expressively complete\nfor recursively enumerable OCQA ontologies.\n
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".