Triple
T8234524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westmont station |
E192370
|
entity |
| Predicate | hasParkingOwner |
P58757
|
FINISHED |
| Object | municipal or public parking |
—
|
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: municipal or public parking | Statement: [Westmont station, hasParkingOwner, municipal or public parking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingOwner Context triple: [Westmont station, hasParkingOwner, municipal or public parking]
-
A.
hasParkingLotOwner
chosen
Indicates that a parking lot is owned or possessed by a specific owner.
-
B.
hasParkOwner
Indicates that an entity serves as the owner or legal controller of a particular park.
-
C.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
D.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
E.
hasParkStatus
Indicates that an entity holds a particular designation or status related to being a park (e.g., national park, city park, protected parkland).
- 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_69ca82db5b90819085d1ad7c2e27bfcc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb782931848190bcc54622f34e06a7 |
completed | March 31, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69cb36b1dea0819091418072501e79c1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:46 p.m.