Triple
T14975794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirkelandet |
E373442
|
entity |
| Predicate | hasNeighbouringIsland |
P19482
|
FINISHED |
| Object | Nordlandet |
E393085
|
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: Nordlandet | Statement: [Kirkelandet, hasNeighbouringIsland, Nordlandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nordlandet Context triple: [Kirkelandet, hasNeighbouringIsland, Nordlandet]
-
A.
Nordlandet
chosen
Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
-
B.
Nordland
Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
-
C.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
-
D.
Nordre Land
Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
-
E.
Vestlandet
Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e8733081908e06b53746eb6eb6 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9692e4fc8190a1194a41fc8a832c |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:51 a.m.