Triple
T29682872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke Point ferry terminal |
E751001
|
entity |
| Predicate | hasPassengerBoardingRamps |
P46229
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Duke Point ferry terminal, hasPassengerBoardingRamps, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerBoardingRamps Context triple: [Duke Point ferry terminal, hasPassengerBoardingRamps, yes]
-
A.
hasPassengerBoardingGates
chosen
Indicates that an entity is associated with or contains one or more passenger boarding gates used for embarking or disembarking passengers.
-
B.
hasVehicleLoadingRamps
Indicates that something is equipped with ramps specifically intended for loading or unloading vehicles.
-
C.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
D.
hasMilitaryRamp
Indicates that a structure or location is equipped with a ramp specifically designed for military use, such as loading, unloading, or deploying military personnel, vehicles, or equipment.
-
E.
hasRunwayOrPad
Indicates that a location possesses a designated runway or launch/landing pad suitable for vehicle operations.
- 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: April 28, 2026, 7:11 p.m.