Triple
T15183735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen main production plant |
E362812
|
entity |
| Predicate | hasParkingFacilitiesFor |
P67493
|
FINISHED |
| Object | employees |
—
|
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: employees | Statement: [Volkswagen main production plant, hasParkingFacilitiesFor, employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingFacilitiesFor Context triple: [Volkswagen main production plant, hasParkingFacilitiesFor, employees]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkingFor
chosen
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
C.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
D.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
E.
hasUndergroundParking
Indicates that a place or building provides parking facilities located below ground level.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006674c088190ba635a78c30f5637 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.