Triple
T17846528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vågsfjorden |
E445676
|
entity |
| Predicate | hasCoastlineOn |
P212
|
FINISHED |
| Object | Hinnøya |
—
|
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: Hinnøya | Statement: [Vågsfjorden, hasCoastlineOn, Hinnøya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hinnøya Context triple: [Vågsfjorden, hasCoastlineOn, Hinnøya]
-
A.
Hinnøya
chosen
Hinnøya is the largest island in mainland Norway, known for its dramatic fjords, mountains, and coastal landscapes in the north of the country.
-
B.
Hornøya
Hornøya is a small Norwegian island in the Barents Sea renowned as an important seabird sanctuary and the easternmost point of mainland Norway’s territory.
-
C.
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.
-
D.
Lindøya
Lindøya is a small, scenic island in the Oslofjord known for its colorful wooden cottages, car-free environment, and popularity as a summer retreat near Oslo.
-
E.
Storøya
Storøya is an island located in the lake Tyrifjorden 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffb35248190a80a428686e06d87 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.