Triple
T2847561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Park Underground station |
E63016
|
entity |
| Predicate | hasJubileeLinePlatforms |
P43383
|
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: [Green Park Underground station, hasJubileeLinePlatforms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJubileeLinePlatforms Context triple: [Green Park Underground station, hasJubileeLinePlatforms, yes]
-
A.
hasSuburbanPlatforms
Indicates that an entity (typically a railway station or transit hub) includes platforms specifically designated for suburban or commuter train services.
-
B.
subwayLine
Indicates that there is a subway line connection or service relationship between the referenced entities.
-
C.
hasShuttleLine
Indicates that there is a shuttle service or route operating between the related entities.
-
D.
hasIslandPlatforms
Indicates that the subject has one or more island-style platforms, typically positioned between tracks and accessible from both sides.
-
E.
hasArchitecturallySignificantStations
Indicates that an entity includes or is associated with stations that are notable or important from an architectural standpoint.
- F. None of above. chosen
Provenance (4 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_69ab4c407c408190857d25e027155ce9 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf3ebbac819090e2bf98ed9fbd02 |
completed | March 7, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69abdd0e86808190bcefffafbd3cd441 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde2cdcc48190827195d3ae70aa19 |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 10:02 p.m.