Triple
T31069408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ridley Terminals |
E791771
|
entity |
| Predicate | nearbyPortAuthority |
P86796
|
FINISHED |
| Object | Prince Rupert Port Authority |
—
|
NE NERFINISHED |
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: Prince Rupert Port Authority | Statement: [Ridley Terminals, nearbyPortAuthority, Prince Rupert Port Authority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyPortAuthority Context triple: [Ridley Terminals, nearbyPortAuthority, Prince Rupert Port Authority]
-
A.
nearInternationalTransportHub
Indicates that one entity is located close to a major international transportation hub, such as an airport, seaport, or central rail terminal.
-
B.
nearbyPortFacility
chosen
Indicates that one entity is located close to or in the immediate vicinity of a port facility.
-
C.
nearbyCityOrPort
Indicates that one location is geographically close to a city or port, typically within a short travel distance.
-
D.
nearbyTerminus
Indicates that one terminus (end point or final stop) is located close to another terminus in space.
-
E.
nearbyMajorStation
Indicates that one location is situated close to a major transportation station (such as a main train, bus, or metro hub).
- 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_69f224cc0c5c81908404f087bff92997 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
Created at: April 29, 2026, 9:01 p.m.