Triple
T494987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qantas |
E10272
|
entity |
| Predicate | safetyReputation |
P11701
|
FINISHED |
| Object | one of the world’s safest airlines |
—
|
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: one of the world’s safest airlines | Statement: [Qantas, safetyReputation, one of the world’s safest airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyReputation Context triple: [Qantas, safetyReputation, one of the world’s safest airlines]
-
A.
associatedWithReputation
chosen
Indicates a relationship where an entity is linked to, influenced by, or characterized in terms of another entity’s reputation or perceived standing.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
reputationWithinLDP
Indicates that an entity holds a particular reputation or standing within a specified Local Development Plan (LDP) context.
-
D.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
E.
securityArrangementsBy
Indicates that one entity is responsible for providing, organizing, or overseeing security arrangements for another entity or situation.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fdd5608190815fa36485df8962 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.