Triple
T17668291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Besseggen ridge |
E440444
|
entity |
| Predicate | hasNameInNorwegian |
P24009
|
FINISHED |
| Object | Besseggen |
—
|
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: Besseggen | Statement: [Besseggen ridge, hasNameInNorwegian, Besseggen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Besseggen Context triple: [Besseggen ridge, hasNameInNorwegian, Besseggen]
-
A.
Besseggen
chosen
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
-
B.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
C.
Waldegg
Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
-
D.
Untereggen
Untereggen is a small Swiss municipality in the canton of St. Gallen, known for its rural character and location in the country’s northeastern region.
-
E.
Herrliberg
Herrliberg is a affluent residential municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland, known for its scenic lakeside setting and proximity to the city of Zurich.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6723d081908eaa57eef6d70bd0 |
completed | April 19, 2026, 6 a.m. |
Created at: April 10, 2026, 9:58 a.m.