Triple
T6119111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camberley railway station |
E136435
|
entity |
| Predicate | hasRealTimeInformationScreens |
P3794
|
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: [Camberley railway station, hasRealTimeInformationScreens, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRealTimeInformationScreens Context triple: [Camberley railway station, hasRealTimeInformationScreens, yes]
-
A.
hasRealTimeInformation
Indicates that up-to-date, continuously refreshed information is available about the related entity or event.
-
B.
hasCustomerInformationScreens
chosen
Indicates that an entity is equipped with screens or displays that present information specifically intended for customers.
-
C.
usedForPassengerInformation
Indicates that something serves the purpose of providing information to passengers.
-
D.
hasRollingStockOnDisplay
Indicates that a location or entity has railway rolling stock (such as locomotives or carriages) exhibited for public viewing.
-
E.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
- 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_69c0089f851c81909e5e189a617dcff6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bee12488190ab217e8956f2f1f3 |
completed | March 22, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c049f9ab3c81909c8ab6466f6a2935 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:14 p.m.