Triple
T35959076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Bannockburn wreck |
E1039946
|
entity |
| Predicate | associatedWithTypeOfVessel |
—
|
GENERATED |
| Object | freighter |
—
|
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: associatedWithTypeOfVessel Context triple: [SS Bannockburn wreck, associatedWithTypeOfVessel, freighter]
-
A.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
B.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
D.
isVesselFor
Indicates that one entity functions as a container or medium specifically used to hold, carry, or convey another entity.
-
E.
namedVesselOf
Indicates that one entity is the specific named vessel (e.g., ship, boat, or craft) associated with or belonging to another entity.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:07 p.m.