Triple
T15302292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kjerag |
E365817
|
entity |
| Predicate | nearestVillage |
P3883
|
FINISHED |
| Object | Lysebotn |
E393076
|
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: Lysebotn | Statement: [Kjerag, nearestVillage, Lysebotn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lysebotn Context triple: [Kjerag, nearestVillage, Lysebotn]
-
A.
Lysebotn
chosen
Lysebotn is a small village at the innermost end of Norway’s Lysefjord, known as a gateway to famous hiking destinations like Kjerag and Preikestolen.
-
B.
Lofthus
Lofthus is a village in Norway’s Hardanger region, known for its fruit orchards, fjord scenery, and role as a gateway to hiking routes like the Hardangervidda plateau.
-
C.
Bremsnes
Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
-
D.
Alstahaug
Alstahaug is a coastal municipality in northern Norway known for its historic church, island landscapes, and maritime heritage.
-
E.
Kjeldebotn
Kjeldebotn is a small village in northern Norway that forms part of the municipality of Ballangen in Nordland county.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ccd575c8190aa43262d3b73ef3c |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe60d4a08190833397c75b56932c |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 3:15 a.m.