Triple
T3750485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms og Finnmark |
E81316
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object | Troms |
E80793
|
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 | Statement: [Troms og Finnmark, formedByMergerOf, Troms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troms Context triple: [Troms og Finnmark, formedByMergerOf, Troms]
-
A.
Troms
chosen
Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
-
B.
Trondenes
Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
-
C.
Nordlandet
Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
-
D.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
-
E.
Volda
Volda is a municipality in Møre og Romsdal county, Norway, known for its fjord landscape, cultural life, and Volda University College.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6d0ac4819092c9a41cc60f518d |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5282a7f0c81908bf7f3d3aa8b0e85 |
completed | March 14, 2026, 9:19 a.m. |
Created at: March 8, 2026, 3:35 p.m.