Triple
T28342091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highgate Underground Station |
E717840
|
entity |
| Predicate | hasDisusedSurfacePlatforms |
P71839
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Highgate Underground Station, hasDisusedSurfacePlatforms, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisusedSurfacePlatforms Context triple: [Highgate Underground Station, hasDisusedSurfacePlatforms, true]
-
A.
hasDisusedPlatforms
chosen
Indicates that an entity (such as a station or facility) possesses one or more platforms that are no longer in active use.
-
B.
hasDisusedUndergroundStation
Indicates that an entity possesses or is associated with an underground station that is no longer in active use.
-
C.
hasTerminatingPlatforms
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
-
D.
hasBusPlatforms
Indicates that a location or facility is equipped with one or more designated platforms for boarding or alighting from buses.
-
E.
hasRailPlatforms
Indicates that an entity is equipped with one or more rail platforms used for boarding or alighting from trains.
- 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: April 28, 2026, 12:40 a.m.