Triple
T25144652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heaton Park tram stop |
E629899
|
entity |
| Predicate | parkAndRideCarPark |
P24860
|
FINISHED |
| Object | Heaton Park Park and Ride |
—
|
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: Heaton Park Park and Ride | Statement: [Heaton Park tram stop, parkAndRideCarPark, Heaton Park Park and Ride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkAndRideCarPark Context triple: [Heaton Park tram stop, parkAndRideCarPark, Heaton Park Park and Ride]
-
A.
parkLocation
Indicates the place or area where something is parked or intended to be parked.
-
B.
hasParkAndRideGarage
Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
-
C.
parkSystem
Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
-
D.
hasParkAndRideFunction
chosen
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.
-
E.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f4684b30a8819088fb9f78020c3e1a |
completed | May 1, 2026, 8:46 a.m. |
| PD | Predicate disambiguation | batch_69f44d8043b081908bbffd7f044b4f26 |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 6:29 a.m.