Triple
T510964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF High Wycombe |
E10605
|
entity |
| Predicate | hasSupportRoleFor |
P6239
|
FINISHED |
| Object | RAF personnel and staff at headquarters |
—
|
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: RAF personnel and staff at headquarters | Statement: [RAF High Wycombe, hasSupportRoleFor, RAF personnel and staff at headquarters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSupportRoleFor Context triple: [RAF High Wycombe, hasSupportRoleFor, RAF personnel and staff at headquarters]
-
A.
supportsRole
Indicates that one entity provides the necessary functionality, resources, or conditions for another entity to perform or occupy a specific role.
-
B.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
C.
servesRole
Indicates that one entity performs, fulfills, or occupies a particular function, position, or responsibility in relation to another entity.
-
D.
hasAuxiliaryRole
chosen
Indicates that an entity serves in a supporting or secondary capacity to another entity or primary role.
-
E.
hasSupporter
Indicates that one entity supports, endorses, or backs another entity.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f165b91c81908c2d2ba15c64b956 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.