Triple
T23779261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grefsen station |
E587763
|
entity |
| Predicate | nearbyTramLine |
P150008
|
FINISHED |
| Object | Oslo Tram line 13 |
—
|
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: Oslo Tram line 13 | Statement: [Grefsen station, nearbyTramLine, Oslo Tram line 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyTramLine Context triple: [Grefsen station, nearbyTramLine, Oslo Tram line 13]
-
A.
nearestCommuterRailLine
Indicates the commuter rail line that is geographically closest to a given location or entity.
-
B.
hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
-
C.
nearestRailwayLine
Indicates that one railway line is the closest in distance to a given location or feature compared to all other railway lines.
-
D.
nearbyMainlineConnection
Indicates that one entity has a mainline connection located in close physical proximity to another entity.
-
E.
servedByTramwayLine
chosen
Indicates that a location or area is provided public transport service by a specific tramway line.
- 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c62ad61c8190a552e88bce2bad1c |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.