Triple
T24418595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitefield tram stop |
E615657
|
entity |
| Predicate | hasParkAndRideSpaces |
P24862
|
FINISHED |
| Object | car park |
—
|
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: car park | Statement: [Whitefield tram stop, hasParkAndRideSpaces, car park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkAndRideSpaces Context triple: [Whitefield tram stop, hasParkAndRideSpaces, car park]
-
A.
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.
-
B.
hasParkAndRideGarage
chosen
Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
-
C.
hasPublicTransitFunction
Indicates that something serves a role or provides a service related to public transportation operations or infrastructure.
-
D.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
E.
hasParkSection
Indicates that one entity includes, contains, or is associated with a specific section or area of a park.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29587b2308190907886b82d8c5129 |
completed | April 29, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:13 a.m.