Triple
T15510656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian National Road 15 |
E368699
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Måløy |
—
|
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: Måløy | Statement: [Norwegian National Road 15, terminus, Måløy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Måløy Context triple: [Norwegian National Road 15, terminus, Måløy]
-
A.
Måløy
chosen
Måløy is a coastal town in western Norway known as a key fishing port and regional commercial center.
-
B.
Hisøy
Hisøy is an island in southern Norway that forms part of the coastal region of Agder, known for its maritime character and proximity to the town of Arendal.
-
C.
Dillingøy
Dillingøy is an island located in southeastern Norway, within the coastal area of Moss in Østfold/Viken county.
-
D.
Kvitsøy
Kvitsøy is a small island municipality in southwestern Norway known for its maritime heritage, lighthouse, and rich coastal fishing grounds.
-
E.
Andøy
Andøy is a municipality and island area in Nordland county, Norway, known for its Arctic landscapes, fishing communities, and whale-watching opportunities.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03fd008708190a3657863eb9ac626 |
completed | April 16, 2026, 1:48 a.m. |
Created at: April 10, 2026, 3:55 a.m.