Triple
T13418041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austvågøy |
E313264
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Gimsøy |
E1050352
|
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: Gimsøy | Statement: [Austvågøy, connectedTo, Gimsøy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gimsøy Context triple: [Austvågøy, connectedTo, Gimsøy]
-
A.
Gimsøy
chosen
Gimsøy is a small coastal village in Norway’s Lofoten archipelago, known for its scenic landscapes and traditional fishing heritage.
-
B.
Kirkøy
Kirkøy is the main inhabited island and administrative center of Norway’s Hvaler municipality, known for its coastal scenery and role as a hub in the Hvaler archipelago.
-
C.
Rolvsøy
Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, Norway.
-
D.
Dillingøy
Dillingøy is an island located in southeastern Norway, within the coastal area of Moss in Østfold/Viken county.
-
E.
Sakrisøy
Sakrisøy is a small, picturesque fishing village island in Norway’s Lofoten archipelago, known for its yellow rorbuer cabins and dramatic mountain backdrop.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb8416c8190a00dde0917c26f51 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ad2c4dc819083d23448d21bb0f3 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:39 p.m.