Triple
T13147078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Å i Lofoten |
E312367
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | Moskenesøya island |
E319755
|
NE FINISHED |
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: Moskenesøya island | Statement: [Å i Lofoten, locatedOn, Moskenesøya island]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moskenesøya island Context triple: [Å i Lofoten, locatedOn, Moskenesøya island]
-
A.
Tromsøya island
Tromsøya island is a Norwegian island in Troms og Finnmark county that hosts the city center of Tromsø and is known for its Arctic location and vibrant cultural life.
-
B.
Moskenesøya
chosen
Moskenesøya is a rugged island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and scenic coastal landscapes.
-
C.
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.
-
D.
Rolvsøy island
Rolvsøy island is a Norwegian island in Østfold county known for its residential communities and proximity to the city of Fredrikstad.
-
E.
Vestvågøya island
Vestvågøya island is a major island in Norway’s Lofoten archipelago, known for its dramatic mountains, fishing villages, and scenic coastal landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bd0f5b08190ab700c5de1c8e138 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d3398b08190a0fc4b6044576e0a |
completed | May 3, 2026, 7:08 p.m. |
Created at: April 9, 2026, 9:10 p.m.