Triple
T16182223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malangen |
E392711
|
entity |
| Predicate | hasNorwegianName |
P1435
|
FINISHED |
| Object | Malangen |
—
|
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: Malangen | Statement: [Malangen, hasNorwegianName, Malangen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malangen Context triple: [Malangen, hasNorwegianName, Malangen]
-
A.
Malangen
chosen
Malangen is a prominent fjord in northern Norway known for its scenic coastal landscapes and proximity to the city of Tromsø in Troms county.
-
B.
Malvik
Malvik is a coastal municipality in central Norway, located in Trøndelag county near the city of Trondheim.
-
C.
Bremanger
Bremanger is a coastal municipality in Vestland county, Norway, known for its rugged fjord landscape, fishing communities, and scenic beaches like Grotlesanden.
-
D.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
E.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205d858c8190802d44e08e3cdcd6 |
completed | April 17, 2026, 11:58 a.m. |
Created at: April 10, 2026, 5:02 a.m.