Triple
T21888794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo International School |
E540481
|
entity |
| Predicate | nearbyArea |
P2064
|
FINISHED |
| Object | Bekkestua |
—
|
NE NERFINISHED |
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: Bekkestua | Statement: [Oslo International School, nearbyArea, Bekkestua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bekkestua Context triple: [Oslo International School, nearbyArea, Bekkestua]
-
A.
Bekkestua
chosen
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Tyssedal
Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
-
C.
Bålsta
Bålsta is a locality in Uppsala County, Sweden, known as the main urban center of Håbo Municipality and a commuter town within the Greater Stockholm region.
-
D.
Steinråa
Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
-
E.
Hasselvika
Hasselvika is a small coastal village in the former Agdenes municipality in Trøndelag county, central Norway.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118ef2b648190bbd78f6b3958d2ee |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 16, 2026, 7:05 p.m.