Triple
T20250412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gvarv |
E498536
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Telemark |
—
|
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: Telemark | Statement: [Gvarv, locatedIn, Telemark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telemark Context triple: [Gvarv, locatedIn, Telemark]
-
A.
Telemark
chosen
Telemark is a historic region and former county in southeastern Norway known for its traditional folk culture, distinctive skiing heritage, and varied landscapes of mountains, forests, and coast.
-
B.
Sälen
Sälen is a Swedish mountain village and popular ski resort area in Dalarna, best known as the traditional starting point of the annual Vasaloppet cross-country ski race.
-
C.
Kvalheim
Kvalheim is a small coastal village in the former Vågsøy municipality in western Norway, known for its scenic North Sea surroundings and traditional fishing community.
-
D.
Trysil
Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
-
E.
Snåsa
Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a79a208190a5a7c0f6515bc393 |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.