Triple
T20745945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class 78 electric multiple unit |
E510582
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Flytoget |
—
|
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: Flytoget | Statement: [Class 78 electric multiple unit, owner, Flytoget]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flytoget Context triple: [Class 78 electric multiple unit, owner, Flytoget]
-
A.
Flytoget
chosen
Flytoget is Norway’s high-speed airport express train service that connects Oslo Airport with Oslo and surrounding areas.
-
B.
FINN eiendom
FINN eiendom is the real estate marketplace section of the Norwegian classifieds website Finn.no, where users can buy, sell, and rent properties.
-
C.
Boende
Boende is a town in the Democratic Republic of the Congo that serves as an important local center of trade and administration in the Tshuapa Province.
-
D.
Hyra
Hyra is the surname of American actress and producer Meg Ryan, known for her roles in popular romantic comedies of the late 20th century.
-
E.
Rom Eiendom
Rom Eiendom is a Norwegian real estate company that manages and develops properties associated with the country’s railway infrastructure.
- 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c212b744819089bc1d47a020bd61 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:33 p.m.