Triple
T33994823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zihuatanejo port |
E871644
|
entity |
| Predicate | typicalVesselTypes |
—
|
GENERATED |
| Object | small fishing boats |
—
|
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: typicalVesselTypes Context triple: [Zihuatanejo port, typicalVesselTypes, small fishing boats]
-
A.
typicalShipTypes
chosen
Indicates that the subject is commonly or characteristically associated with the specified types or categories of ships.
-
B.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
sponsoredVesselType
Indicates that one entity has provided sponsorship or financial backing specifically for a vessel of a given type.
-
E.
typicalVesselMaterial
Indicates the material that is most commonly or characteristically used to make a given vessel.
- 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:50 a.m.