Triple
T3442287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kven language |
E72591
|
entity |
| Predicate | region |
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: [Kven language, region, Troms og Finnmark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troms og Finnmark Context triple: [Kven language, region, 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.
Møre og Romsdal
Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
-
C.
Nordland
Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
-
D.
Trøndelag
Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
-
E.
Rogaland
Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
- 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_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba28ec448190a6a07c5f16235fe3 |
completed | March 8, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e563dc08190a9c3a3ec725cb1d6 |
completed | March 13, 2026, 3:02 a.m. |
Created at: March 8, 2026, 3:16 p.m.