Triple
T13398201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moskenesøya |
E319755
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Nusfjord |
E313265
|
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: Nusfjord | Statement: [Moskenesøya, hasVillage, Nusfjord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nusfjord Context triple: [Moskenesøya, hasVillage, Nusfjord]
-
A.
Nusfjord
chosen
Nusfjord is a historic fishing village in Norway’s Lofoten archipelago, known for its well-preserved wooden rorbuer cabins and scenic coastal setting.
-
B.
Balsfjord
Balsfjord is a fjord in northern Norway known for its scenic Arctic landscapes and proximity to the city of Tromsø.
-
C.
Flekkefjord
Flekkefjord is a coastal town in southern Norway known for its historic wooden architecture, maritime heritage, and picturesque fjord setting.
-
D.
Tysfjord
Tysfjord is a dramatic fjord in Nordland county in Northern Norway, known for its steep mountains, deep waters, and rich marine and Sami cultural heritage.
-
E.
Sigerfjord
Sigerfjord is a small coastal village in northern Norway, situated on the island of Hinnøya in the Vesterålen region.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d9e7348190844e11dd6cbd13b0 |
completed | April 12, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3cf863fc81908723f7f6b3d45510 |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 9, 2026, 9:34 p.m.