Triple
T19717589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian Airways |
E473518
|
entity |
| Predicate | safetyRegulationScope |
P93778
|
FINISHED |
| Object | international |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: international | Statement: [Georgian Airways, safetyRegulationScope, international]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRegulationScope Context triple: [Georgian Airways, safetyRegulationScope, international]
-
A.
hasRegulationScope
chosen
Indicates that a regulation applies to, or governs, a specified scope, domain, or area of relevance.
-
B.
safetyRegulationEffect
Indicates how a safety regulation influences or changes the conditions, behaviors, or outcomes associated with the regulated entities.
-
C.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
D.
safetyRegulationChange
Indicates a modification, update, or revision to existing safety regulations governing how something must be designed, operated, or managed.
-
E.
subjectToRegulation
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440ec9e881909b75c0ebefab827f |
completed | April 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.