Triple
T30807731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A201 road |
E784549
|
entity |
| Predicate | hasNearbyRailwayStations |
P31869
|
FINISHED |
| Object | King's Cross railway station |
—
|
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: King's Cross railway station | Statement: [A201 road, hasNearbyRailwayStations, King's Cross railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRailwayStations Context triple: [A201 road, hasNearbyRailwayStations, King's Cross railway station]
-
A.
hasNearbyRailwayStation
chosen
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
B.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
C.
nearbyMajorStation
Indicates that one location is situated close to a major transportation station (such as a main train, bus, or metro hub).
-
D.
nearbyHeritageStation
Indicates that one entity is located close to a heritage (historically or culturally significant) station.
-
E.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to another entity.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69febce5877c8190a5e000ef5331ec88 |
completed | May 9, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69febad1cd588190abc7686bcb39a371 |
completed | May 9, 2026, 4:40 a.m. |
Created at: April 29, 2026, 8:43 p.m.