Triple
T1743042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashton West tram stop |
E38273
|
entity |
| Predicate | parkAndRideSpaces |
P21999
|
FINISHED |
| Object | 194 |
—
|
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: 194 | Statement: [Ashton West tram stop, parkAndRideSpaces, 194]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkAndRideSpaces Context triple: [Ashton West tram stop, parkAndRideSpaces, 194]
-
A.
parkSystem
Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
-
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.
numberOfParkingSpaces
chosen
Indicates the total count of parking spaces associated with a particular entity or location.
-
E.
parkingStructure
Indicates that one entity is a parking facility or structure associated with another entity (such as a building, location, or organization).
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.