Triple
T34739573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbey Wood (Elizabeth line) station |
E1001457
|
entity |
| Predicate | hasTerminalPlatforms |
P15094
|
FINISHED |
| Object | 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: 2 | Statement: [Abbey Wood (Elizabeth line) station, hasTerminalPlatforms, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerminalPlatforms Context triple: [Abbey Wood (Elizabeth line) station, hasTerminalPlatforms, 2]
-
A.
hasTerminatingPlatforms
chosen
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
-
B.
hasNumberOfPlatforms
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
C.
hasSidePlatformCount
Indicates the number of side platforms associated with an entity, such as a station or stop.
-
D.
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.
-
E.
hasTerminalFacility
Indicates that an entity possesses or includes a terminal facility used as an endpoint for transport, communication, or related operations.
- 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_69f76daf739881909ed3554f98a2b433 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: May 3, 2026, 3:59 p.m.