Triple
T21349572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upton Park Underground station |
E526436
|
entity |
| Predicate | hasNearbyBusServices |
P15095
|
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: [Upton Park Underground station, hasNearbyBusServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyBusServices Context triple: [Upton Park Underground station, hasNearbyBusServices, yes]
-
A.
operatorOfNearbyTransit
Indicates that an entity operates or manages a public transit service located in close geographic proximity to another specified entity.
-
B.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
-
C.
hasBusServices
Indicates that one location or entity is served by bus routes or bus transportation provided by another.
-
D.
hasAdjacentBusStation
chosen
Indicates that one location has a bus station situated directly next to or very near it.
-
E.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8ad30512081909012ce318fa67679 |
completed | April 22, 2026, 11:12 a.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:03 p.m.