Triple
T7142859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Østerås |
E166490
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bærum |
E186288
|
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: Bærum | Statement: [Østerås, locatedIn, Bærum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bærum Context triple: [Østerås, locatedIn, Bærum]
-
A.
Bærum
chosen
Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
-
B.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
C.
Klepp
Klepp is a coastal agricultural municipality located on the Jæren plain in Rogaland county in southwestern Norway.
-
D.
Sandnes
Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
-
E.
Ullensaker
Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e779ace48190be9c33750e60a79e |
completed | March 27, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eec29d8c81909d9123b48b195f98 |
completed | March 28, 2026, 3:07 p.m. |
Created at: March 27, 2026, 2:45 p.m.