Triple
T18807597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SL metro |
E459919
|
entity |
| Predicate | numberOfSurfaceStations |
P1301
|
FINISHED |
| Object | 53 |
—
|
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: 53 | Statement: [SL metro, numberOfSurfaceStations, 53]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSurfaceStations Context triple: [SL metro, numberOfSurfaceStations, 53]
-
A.
numberOfStations
chosen
Indicates the total count of stations associated with or contained by a given entity.
-
B.
isSurfaceStation
Indicates that the station is located at or on the surface (e.g., ground level) rather than being underground, elevated, or otherwise non-surface.
-
C.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
D.
numberOfSites
Indicates the total count of distinct sites associated with or involved in the given entity or context.
-
E.
relatedStationNumber
Indicates that there is an associated or corresponding station identified by a particular station number.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d8ab9c819097834eac798ce810 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.