Triple
T33088722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Convoy PQ 17 |
E846712
|
entity |
| Predicate | numberOfNavalEscorts |
—
|
GENERATED |
| Object | 6 destroyers and other escorts |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNavalEscorts Context triple: [Convoy PQ 17, numberOfNavalEscorts, 6 destroyers and other escorts]
-
A.
numberOfNaves
Indicates the specific count of naves (longitudinal sections) that a building, typically a church, possesses.
-
B.
typeOfVesselEscorted
Indicates the specific kind of vessel that is being accompanied or protected in an escorting relationship.
-
C.
numberOfShips
chosen
Indicates the quantity of ships associated with a given entity or situation.
-
D.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
E.
navalForceInvolved
Indicates that a naval military force participates in, contributes to, or is otherwise involved in a specified event or operation.
- F. None of above.
Provenance (1 batch)
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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:26 a.m.