Triple
T19068569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian National Road 23 |
E466730
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Vestby |
—
|
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: Vestby | Statement: [Norwegian National Road 23, connects, Vestby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vestby Context triple: [Norwegian National Road 23, connects, Vestby]
-
A.
Vestby
chosen
Vestby is a municipality in Viken county in southeastern Norway, known for its coastal location along the Oslofjord and proximity to Oslo.
-
B.
Viby
Viby is a residential district and locality within the suburban municipality of Sollentuna in the Stockholm region of Sweden.
-
C.
Viby
Viby is a suburban neighborhood in the southern part of Aarhus, Denmark, known for its residential areas, local commerce, and transport connections to the city center.
-
D.
Vejby
Vejby is a small town in North Zealand, Denmark, known for its rural surroundings and access to the Gribskov railway line.
-
E.
Iveland
Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19b94d08190865b62d98f718bb0 |
completed | April 20, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:03 p.m.