Triple
T28342108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highgate Underground Station |
E717840
|
entity |
| Predicate | hasOriginalSurfaceStationName |
P49136
|
FINISHED |
| Object | Highgate (LNER) |
—
|
NE NERFINISHED |
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: Highgate (LNER) | Statement: [Highgate Underground Station, hasOriginalSurfaceStationName, Highgate (LNER)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalSurfaceStationName Context triple: [Highgate Underground Station, hasOriginalSurfaceStationName, Highgate (LNER)]
-
A.
hasOriginalVesselName
Indicates that an entity (such as a vessel) is associated with its original, historically first-assigned name.
-
B.
hasOriginalNameOf
Indicates that one entity is the original or earlier name from which another entity’s current or later name is derived.
-
C.
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.
-
D.
originalStationLocation
Indicates the location where a station was initially established or first situated.
-
E.
formerStationNameFor
chosen
Indicates that one station name was previously used as the official name for another station.
- 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_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 28, 2026, 12:40 a.m.