Triple
T15352847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadsel Bridge |
E367095
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Børøya island |
—
|
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: Børøya island | Statement: [Hadsel Bridge, serves, Børøya island]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Børøya island Context triple: [Hadsel Bridge, serves, Børøya island]
-
A.
Børøya
chosen
Børøya is a small Norwegian island in Nordland county that lies near Hadseløya and is part of the Vesterålen archipelago.
-
B.
Storøya island
Storøya island is a small, remote Arctic island in the Svalbard archipelago of Norway, known for its polar wildlife and harsh, icy environment.
-
C.
Rolvsøy island
Rolvsøy island is a Norwegian island in Østfold county known for its residential communities and proximity to the city of Fredrikstad.
-
D.
Bjørnøya
Bjørnøya is a remote, largely uninhabited Norwegian island in the Barents Sea, known for its rugged cliffs, rich birdlife, and role as the southernmost part of the Svalbard archipelago.
-
E.
Brønnøya
Brønnøya is a scenic island in the Oslofjord known for its holiday homes, nature trails, and car-free environment, located within the municipality of Asker in Norway.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2a8e88819093e4b7479b2c80cd |
completed | April 16, 2026, 1:40 a.m. |
Created at: April 10, 2026, 3:17 a.m.