Triple
T26440796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eiksmarka station |
E665079
|
entity |
| Predicate | suburbanStation |
P158003
|
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: [Eiksmarka station, suburbanStation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanStation Context triple: [Eiksmarka station, suburbanStation, yes]
-
A.
isSuburbanStationOf
Indicates that a station is located in a suburban area and functionally serves as a subsidiary or outlying station of a main or central station.
-
B.
isSuburbanStationFor
chosen
Indicates that a station primarily serves a suburban area or functions as a transit hub for suburban commuters relative to a larger urban center.
-
C.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
D.
hasSuburbanTerminus
Indicates that a transportation route or service ends at a terminus located in a suburban area.
-
E.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
- 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_69ee883c851881909e2ab04efbb3c5fe |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6121ae1a0819083492db2e6863175 |
completed | May 2, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 11:58 p.m.