Triple
T2329092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Plains station |
E48358
|
entity |
| Predicate | hasKissAndRideArea |
P33499
|
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: [White Plains station, hasKissAndRideArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKissAndRideArea Context triple: [White Plains station, hasKissAndRideArea, yes]
-
A.
hasKissAndRide
chosen
Indicates that a location provides a designated area where passengers can be briefly dropped off or picked up, typically by car, without long-term parking.
-
B.
hasParkAndRideFunction
Indicates that a location or facility serves as a park-and-ride, where people can park vehicles and transfer to another mode of transport for the rest of their journey.
-
C.
hasParkAndRideGarage
Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
-
D.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
E.
hasRestAreas
Indicates that a route, location, or facility includes one or more designated rest areas available for use.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abcc30c5e881908c5d526d7e7491d0 |
completed | March 7, 2026, 6:56 a.m. |
| PD | Predicate disambiguation | batch_69abc5926d048190a535e3f23d41de2a |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:50 p.m.