Triple
T296620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Australian Air Force |
E6104
|
entity |
| Predicate | hasPersonnel |
P1211
|
FINISHED |
| Object | tens of thousands of active personnel |
—
|
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: tens of thousands of active personnel | Statement: [Royal Australian Air Force, hasPersonnel, tens of thousands of active personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPersonnel Context triple: [Royal Australian Air Force, hasPersonnel, tens of thousands of active personnel]
-
A.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
-
B.
hasPerson
Indicates that an entity is associated with or includes a specific person.
-
C.
staffIncluded
Indicates that staff members are included or provided as part of the associated entity, service, or arrangement.
-
D.
employedPeople
chosen
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
E.
notablePersonnel
Indicates that the subject has associated individuals who are particularly important, distinguished, or prominent in relation to it.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea4778cc8190be7b648a82542891 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e937af888190a0960708f09ae033 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.