Triple
T38243656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ExpoCité grounds |
E1013834
|
entity |
| Predicate | hasParkingCapacityFor |
P1708
|
FINISHED |
| Object | thousands of vehicles |
—
|
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: thousands of vehicles | Statement: [ExpoCité grounds, hasParkingCapacityFor, thousands of vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingCapacityFor Context triple: [ExpoCité grounds, hasParkingCapacityFor, thousands of vehicles]
-
A.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
B.
hasParking
chosen
Indicates that a place or facility provides designated parking space(s) available for use.
-
C.
hasOnscreenParkingLot
Indicates that an entity features or includes a parking lot that is visible or present on screen.
-
D.
hasAccessibleParking
Indicates that a place or facility provides parking spaces that are accessible to people with disabilities.
-
E.
hasParkingConnection
Indicates that one entity is linked to another through a parking-related connection, such as shared access, adjacency, or functional association with parking facilities.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00781b749c8190921c46e110cae0b0 |
completed | May 10, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_6a0077df3c8481909fabc9e84f5936e3 |
completed | May 10, 2026, 12:19 p.m. |
Created at: May 3, 2026, 4:30 p.m.