Triple
T2032596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windermere railway station |
E44550
|
entity |
| Predicate | hasTicketBarriers |
P1973
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Windermere railway station, hasTicketBarriers, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketBarriers Context triple: [Windermere railway station, hasTicketBarriers, no]
-
A.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
hasTicketHall
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
-
C.
hasTicketRequirement
Indicates that an entity is subject to a specific ticket or admission requirement in order for access, participation, or use to be allowed.
-
D.
hasFaregates
chosen
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
E.
hasConcessions
Indicates that one entity provides or contains concession facilities, services, or rights (such as food, drink, or merchandise sales) for another entity or within a given context.
- 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.