Triple
T27368893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Risløkka station |
E690251
|
entity |
| Predicate | hasNeighboringStation |
P181057
|
FINISHED |
| Object | Vollebekk 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: Vollebekk station | Statement: [Risløkka station, hasNeighboringStation, Vollebekk station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighboringStation Context triple: [Risløkka station, hasNeighboringStation, Vollebekk station]
-
A.
hasAdjacentStations
chosen
Indicates that two stations are directly next to each other in a sequence or network, with no other station in between.
-
B.
hasAdjacentStationOnAC
Indicates that one station is directly next to another station along the AC line or route.
-
C.
hasAdjacentStationOnG
Indicates that one station is directly next to another station along line G in the network.
-
D.
hasAdjacentStationOnE
Indicates that one station is directly adjacent to another station on the east side.
-
E.
hasAdjacentStationOnM
Indicates that one station is directly next to another station along metro line M, with no other stations in between.
- 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_69ef51ff826081909e42c8e2bfb97941 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: April 27, 2026, 12:18 p.m.