Triple
T1067874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria (ship) |
E23253
|
entity |
| Predicate | survivingShipsOfFleet |
P24302
|
FINISHED |
| Object | only ship to complete the circumnavigation |
—
|
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: only ship to complete the circumnavigation | Statement: [Victoria (ship), survivingShipsOfFleet, only ship to complete the circumnavigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivingShipsOfFleet Context triple: [Victoria (ship), survivingShipsOfFleet, only ship to complete the circumnavigation]
-
A.
shipsSunkOrTotalLoss
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
B.
otherShipsInFleet
Indicates that the subject ship and the object ship are distinct members of the same fleet.
-
C.
navalFleet
Indicates a relationship where multiple naval vessels are organized and operate together as a coordinated maritime military force.
-
D.
survivingAircraftCount
Indicates the number of aircraft that remain operational or intact after a specified event, condition, or time period.
-
E.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
- F. None of above. chosen
Provenance (4 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b9e1047481909af1cf8df2a01fff |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b736f1e881909bace735b38c0ade |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b9df0a308190a0d87dcd8afe58bc |
completed | March 1, 2026, 10:12 p.m. |
Created at: March 1, 2026, 7:42 p.m.