Triple
T23544532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hauketo Station |
E577852
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Vy |
—
|
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: Vy | Statement: [Hauketo Station, operator, Vy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vy Context triple: [Hauketo Station, operator, Vy]
-
A.
Vy
chosen
Vy is a major Norwegian railway and public transport company operating regional, intercity, and commuter train services across Norway and parts of Sweden.
-
B.
VY
VY is the IATA airline designator assigned to Vueling, a Spanish low-cost carrier based in Barcelona.
-
C.
YV
YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
-
D.
V
V is the stock ticker symbol for Visa Inc., a leading global payments technology company.
-
E.
V
V is a television miniseries best known as a 1980s science fiction drama about an alien invasion and human resistance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1ef55c8190a93c33e704ec3b5a |
completed | April 29, 2026, 7:07 a.m. |
Created at: April 17, 2026, 6:11 p.m.