Triple
T30316533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kentish Town Road |
E771068
|
entity |
| Predicate | hasNearbyOvergroundLine |
P197625
|
FINISHED |
| Object | London Overground |
—
|
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: London Overground | Statement: [Kentish Town Road, hasNearbyOvergroundLine, London Overground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyOvergroundLine Context triple: [Kentish Town Road, hasNearbyOvergroundLine, London Overground]
-
A.
hasSubwayLineAboveOrBelow
Indicates that one subway line is physically located above or below another subway line, such as on different levels of a transit system.
-
B.
hasOverpassOrSubway
Indicates that one location is connected to or accessible from another via an overpass or a subway passage.
-
C.
nearUndergroundLine
Indicates that one entity is located close in distance to an underground (subway/metro) line.
-
D.
hasNearbyUndergroundStationEntrance
Indicates that one entity is located close to an entrance of an underground (subway/metro) station.
-
E.
hasAdjacentStationOnOverground
Indicates that one station is directly next to another station on an overground rail line.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
| PDg | Predicate description generation | batch_69fe9fb88db08190a8f4af350633330e |
completed | May 9, 2026, 2:45 a.m. |
Created at: April 29, 2026, 7:51 p.m.