Triple
T17504748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karmsundet |
E426283
|
entity |
| Predicate | separates |
P1175
|
FINISHED |
| Object | Karmøy |
—
|
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: Karmøy | Statement: [Karmsundet, separates, Karmøy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karmøy Context triple: [Karmsundet, separates, Karmøy]
-
A.
Karmøy
chosen
Karmøy is a large island and municipality in Rogaland county, Norway, known for its coastal fishing communities, maritime heritage, and historic Viking sites.
-
B.
Mosterøy
Mosterøy is an island in Norway known for its coastal landscape and traditional West Norwegian island community.
-
C.
Rennesøy
Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
-
D.
Skjervøy
Skjervøy is a coastal fishing town and island community in northern Norway, known for its Arctic scenery and rich marine life.
-
E.
Kvitsøy
Kvitsøy is a small island municipality in southwestern Norway known for its maritime heritage, lighthouse, and rich coastal fishing grounds.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45214d44c8190b1bf04bf24ab8e81 |
completed | April 19, 2026, 3:55 a.m. |
Created at: April 10, 2026, 5:48 a.m.