Triple
T15760404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibestad |
E382080
|
entity |
| Predicate | hasCoastlineOn |
P212
|
FINISHED |
| Object | Vågsfjorden |
—
|
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: Vågsfjorden | Statement: [Ibestad, hasCoastlineOn, Vågsfjorden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vågsfjorden Context triple: [Ibestad, hasCoastlineOn, Vågsfjorden]
-
A.
Vågsfjorden
chosen
Vågsfjorden is a fjord in northern Norway known for its scenic coastal landscapes and as a maritime hub for surrounding towns and islands.
-
B.
Vadheimsfjorden
Vadheimsfjorden is a narrow Norwegian fjord known for its steep surrounding mountains and scenic coastal landscape.
-
C.
Voldafjorden
Voldafjorden is a fjord in western Norway known for its steep surrounding mountains and proximity to the town of Volda in Møre og Romsdal county.
-
D.
Kvæfjorden
Kvæfjorden is a fjord in Troms county in northern Norway, known for its scenic coastal landscape and surrounding mountainous terrain.
-
E.
Langfjorden
Langfjorden is a notable fjord in Norway’s Møre og Romsdal county, characterized by its deep waters and steep surrounding mountains.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b52c548190a0ffa4493a4eb15c |
completed | April 16, 2026, 3 a.m. |
Created at: April 10, 2026, 4:47 a.m.