Triple
T20636738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alvdal |
E507103
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Tynset |
—
|
NE NERFINISHED |
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: Tynset | Statement: [Alvdal, neighboringMunicipality, Tynset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tynset Context triple: [Alvdal, neighboringMunicipality, Tynset]
-
A.
Tynset
chosen
Tynset is a rural municipality in Innlandet county, Norway, known for its vast mountain landscapes, agriculture, and role as a regional service center in the Østerdalen valley.
-
B.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
-
C.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Trysil
Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad1089448190b936de6fd29c8350 |
completed | April 20, 2026, 10:47 p.m. |
Created at: April 16, 2026, 11:42 a.m.