Triple
T7793265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gressholmen |
E180232
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Bygdøy |
E126345
|
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: Bygdøy | Statement: [Gressholmen, hasViewOf, Bygdøy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bygdøy Context triple: [Gressholmen, hasViewOf, Bygdøy]
-
A.
Bygdøy peninsula
chosen
The Bygdøy peninsula is a scenic and affluent area in Oslo known for its beaches, royal estate, and several of Norway’s most important museums, including the Viking Ship Museum and the Fram Museum.
-
B.
Marstrand
Marstrand is a historic seaside town and popular sailing destination on Sweden’s west coast, known for its fortress and picturesque archipelago setting.
-
C.
Askøy
Askøy is a large island and municipality on Norway’s west coast, situated near Bergen and known for its coastal landscapes and commuter links to the city.
-
D.
Kvitsøy
Kvitsøy is a small island municipality in southwestern Norway known for its maritime heritage, lighthouse, and rich coastal fishing grounds.
-
E.
Nøtterøy
Nøtterøy is a large, populated island and former municipality in Vestfold, Norway, situated in the Oslofjord and known for its coastal landscapes and residential communities.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae939c7388190b36d3e746be27a4d |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a00b5948190a8e6184353bbd233 |
completed | March 31, 2026, 5:22 a.m. |
Created at: March 30, 2026, 4:31 p.m.