Triple
T23230949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luster |
E581151
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Høyanger |
—
|
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: Høyanger | Statement: [Luster, borders, Høyanger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Høyanger Context triple: [Luster, borders, Høyanger]
-
A.
Høyanger
chosen
Høyanger is a small industrial village and municipality in Vestland county, western Norway, known for its hydropower-based aluminum production and dramatic fjord landscape.
-
B.
Orkanger
Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
-
C.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
-
D.
Hølen
Hølen is a small historic village in Viken county, Norway, known for its past timber industry and picturesque setting along the Såna river.
-
E.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
- 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f19231ef908190a791b4967916a66f |
completed | April 29, 2026, 5:08 a.m. |
Created at: April 17, 2026, 4:09 p.m.