Triple
T2032597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windermere railway station |
E44550
|
entity |
| Predicate | hasStationCarHireFacilities |
P6090
|
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: [Windermere railway station, hasStationCarHireFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationCarHireFacilities Context triple: [Windermere railway station, hasStationCarHireFacilities, yes]
-
A.
hasRentalCarCenter
chosen
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
-
B.
hasTaxiStand
Indicates that a location or facility includes or is served by a designated taxi stand area where taxis can wait for passengers.
-
C.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
D.
hasParkAndRideFunction
Indicates that a location or facility serves as a park-and-ride, where people can park vehicles and transfer to another mode of transport for the rest of their journey.
-
E.
hasRideSystem
Indicates that one entity (typically an attraction or ride) uses or is associated with a particular ride system or ride mechanism.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9313134819088133fb69b8f606f |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a8125881909c0cb58b777c1faa |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.