Triple
T25147499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgrave railway station |
E629974
|
entity |
| Predicate | hasIslandPlatformNumber |
P18595
|
FINISHED |
| Object | Platform 1/2 |
—
|
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: Platform 1/2 | Statement: [Belgrave railway station, hasIslandPlatformNumber, Platform 1/2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIslandPlatformNumber Context triple: [Belgrave railway station, hasIslandPlatformNumber, Platform 1/2]
-
A.
hasIslandPlatforms
chosen
Indicates that the subject has one or more island-style platforms, typically positioned between tracks and accessible from both sides.
-
B.
hasPlatformNumber
Indicates that a location or service is associated with a specific platform identified by a platform number.
-
C.
hasIslandPlatformAccess
Indicates that access is provided to or from an island platform, typically located between tracks and reachable by passengers.
-
D.
hasSidePlatformCount
Indicates the number of side platforms associated with an entity, such as a station or stop.
-
E.
hasBayPlatforms
Indicates that a station or terminal is equipped with bay platforms, where tracks end in a dead-end configuration and trains enter and exit from the same direction.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 6:30 a.m.