Triple
T5944532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordstrand district |
E132245
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object | Sæter |
E547412
|
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: Sæter | Statement: [Nordstrand district, administrativeCentre, Sæter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sæter Context triple: [Nordstrand district, administrativeCentre, Sæter]
-
A.
Sagene
Sagene is a central district in Oslo, Norway, known for its historic industrial heritage along the Akerselva river and its mix of old workers’ housing and modern urban development.
-
B.
Sæbø
Sæbø is a small Norwegian village known for its scenic location amid steep mountains and fjord landscapes in western Norway.
-
C.
Sokndal
Sokndal is a coastal municipality in Rogaland county in southwestern Norway, known for its rugged coastline, historic settlements, and distinctive geological landscapes.
-
D.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
E.
Etterstad
chosen
Etterstad is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and proximity to the city center.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03937b4a88190819a1fd63fc3d3ed |
completed | March 22, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c67c31d3848190b8619263cf76e45e |
completed | March 27, 2026, 12:46 p.m. |
Created at: March 22, 2026, 4:01 p.m.