Triple
T19802415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midt-Telemark |
E475714
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Kviteseid |
—
|
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: Kviteseid | Statement: [Midt-Telemark, borderedBy, Kviteseid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kviteseid Context triple: [Midt-Telemark, borderedBy, Kviteseid]
-
A.
Kviteseid
chosen
Kviteseid is a rural municipality in southern Norway known for its lakeside landscapes, traditional Telemark culture, and historic role as a regional trading and transport hub.
-
B.
Kjørnes
Kjørnes is a residential area and neighborhood within the municipality of Sogndal in Vestland county, Norway.
-
C.
Fjeldstad
Fjeldstad is a Norwegian surname most notably associated with conductor and violinist Øivin Fjeldstad.
-
D.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
E.
Kvikne
Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654257cb4819096fb2aa5d1f7fbb0 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.