Triple
T3579244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysefjord |
E75760
|
entity |
| Predicate | hasLandmark |
P105
|
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: [Lysefjord, hasLandmark, Lysebotn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lysebotn Context triple: [Lysefjord, hasLandmark, 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.
Bjørvika
Bjørvika is a waterfront neighborhood in central Oslo, Norway, known for its modern architecture and cultural institutions such as the Munch Museum and the Oslo Opera House.
-
E.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0defe14819095a337a840e33300 |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51203d6148190a9946a3f274e21a5 |
completed | March 14, 2026, 7:45 a.m. |
Created at: March 8, 2026, 3:21 p.m.