Triple
T4631333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenside station |
E101422
|
entity |
| Predicate | hasParkingLot |
P1708
|
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: [Glenside station, hasParkingLot, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingLot Context triple: [Glenside station, hasParkingLot, yes]
-
A.
hasParking
chosen
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
C.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
D.
hasParkingApron
Indicates that a location or facility includes a designated parking apron area for vehicles or aircraft.
-
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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a32d6408190962e60b9bce7560d |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.