Triple
T69614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunfermline Queen Margaret railway station |
E1391
|
entity |
| Predicate | hasCarPark |
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: [Dunfermline Queen Margaret railway station, hasCarPark, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarPark Context triple: [Dunfermline Queen Margaret railway station, hasCarPark, yes]
-
A.
hasParking
chosen
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
C.
hasParkAlongBank
Indicates that a park is located adjacent to or running alongside the bank of a water body.
-
D.
hasHouse
Indicates that one entity possesses, owns, or is provided with a house in relation to another entity.
-
E.
hasNumberOfHouses
Indicates the quantity of houses associated with a given entity.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.