Triple
T3009944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitefield Metrolink stop |
E82191
|
entity |
| Predicate | parkAndRideCapacity |
P21999
|
FINISHED |
| Object | over 200 spaces |
—
|
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: over 200 spaces | Statement: [Whitefield Metrolink stop, parkAndRideCapacity, over 200 spaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkAndRideCapacity Context triple: [Whitefield Metrolink stop, parkAndRideCapacity, over 200 spaces]
-
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
Indicates that a location includes a parking facility where people can park their vehicles and transfer to public transit services.
-
C.
numberOfParkingSpaces
chosen
Indicates the total count of parking spaces associated with a particular entity or location.
-
D.
parkSystem
Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
-
E.
parkingRequirement
Indicates the specified conditions or obligations related to providing or using parking associated with an entity or activity.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a4ccbf08190a7580c9e758804d0 |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.