Triple
T2592771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exhibition GO Station |
E58159
|
entity |
| Predicate | hasPassengerPickUpDropOff |
P40067
|
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: [Exhibition GO Station, hasPassengerPickUpDropOff, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerPickUpDropOff Context triple: [Exhibition GO Station, hasPassengerPickUpDropOff, yes]
-
A.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
B.
hasDropOffArea
Indicates that an entity provides a designated area where items, passengers, or goods can be temporarily left or unloaded.
-
C.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
D.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
-
E.
hasTaxiStand
Indicates that a location or facility includes or is served by a designated taxi stand area where taxis can wait for passengers.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd426e2d4819081a07920b4d2a1cc |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:49 p.m.