Triple
T15693959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alta Airport |
E380406
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Troms og Finnmark |
E81316
|
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: Troms og Finnmark | Statement: [Alta Airport, locatedIn, Troms og Finnmark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troms og Finnmark Context triple: [Alta Airport, locatedIn, Troms og Finnmark]
-
A.
Troms og Finnmark
chosen
Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
-
B.
Finnmark
Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
-
C.
Hålogaland
Hålogaland is a historical region in northern Norway traditionally encompassing parts of what are now Troms and Nordland counties.
-
D.
Nordland county
Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
-
E.
Møre og Romsdal
Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4f5a888190bd3681bcb9bbc02f |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bafb761881908e7a891ef390982a |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 4:44 a.m.