Triple
T25911955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mortensrud station |
E652918
|
entity |
| Predicate | hasTicketZoneOperator |
P165015
|
FINISHED |
| Object | Ruter |
—
|
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: Ruter | Statement: [Mortensrud station, hasTicketZoneOperator, Ruter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketZoneOperator Context triple: [Mortensrud station, hasTicketZoneOperator, Ruter]
-
A.
hasTicketingAuthority
Indicates that an entity possesses the official power or permission to issue, manage, or control tickets for an event, service, or system.
-
B.
hasParkOperator
Indicates that a park is operated or managed by a specific organization or individual.
-
C.
hasTicket
Indicates that an entity possesses or holds a ticket, typically granting access, entry, or a right to a service or event.
-
D.
hasTicketAccess
Indicates that an entity is permitted to view, use, or manage a particular ticket or set of tickets.
-
E.
hasCinemaOperator
Indicates that a cinema is operated, managed, or run by a specific organization or individual.
- 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_69e7ab3e025c819086771607157f0015 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 22, 2026, 8:30 a.m.