Triple
T6266139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fjord City |
E140417
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Bjørvika |
E155981
|
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: Bjørvika | Statement: [Fjord City, hasPart, Bjørvika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bjørvika Context triple: [Fjord City, hasPart, Bjørvika]
-
A.
Bjørvika
chosen
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.
-
B.
Drøbak
Drøbak is a coastal town in southeastern Norway known for its historic harbor, charming wooden houses, and role as a gateway to the Oslofjord.
-
C.
Tingvoll
Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
-
D.
Kjelsås
Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
-
E.
Vikersund
Vikersund is a village in Modum municipality in Buskerud, Norway, best known for hosting one of the world’s largest ski flying hills, Vikersundbakken.
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0639fdad081908492c44d369df8c5 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8108dda308190bb3b7209efe132bb |
completed | March 28, 2026, 5:31 p.m. |
Created at: March 22, 2026, 4:25 p.m.