Triple
T3000784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry DeWolf-class offshore patrol vessel |
E81180
|
entity |
| Predicate | plannedShips |
P21287
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Harry DeWolf-class offshore patrol vessel, plannedShips, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedShips Context triple: [Harry DeWolf-class offshore patrol vessel, plannedShips, 6]
-
A.
numberOfPlannedShips
chosen
Indicates the total count of ships that are intended or scheduled to be built, deployed, or used according to a plan.
-
B.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
C.
componentShip
Indicates that one entity is a physical or logical component or part of another entity, such that the whole is composed of or depends on that component.
-
D.
otherShipsInFleet
Indicates that the subject ship and the object ship are distinct members of the same fleet.
-
E.
notableShip
Indicates that there is a notable or significant ship associated with the subject 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1022e48190afee77db94635ff2 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.