Triple
T23475041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nannestad |
E570237
|
entity |
| Predicate | hasNeighbor |
P5707
|
FINISHED |
| Object | Oslo Airport Gardermoen area |
—
|
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: Oslo Airport Gardermoen area | Statement: [Nannestad, hasNeighbor, Oslo Airport Gardermoen area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo Airport Gardermoen area Context triple: [Nannestad, hasNeighbor, Oslo Airport Gardermoen area]
-
A.
Gardermoen
chosen
Gardermoen is a major Norwegian air base and aviation hub that has historically served as an important military airfield for Norway.
-
B.
Gardermoen (Vestby)
Gardermoen (Vestby) is a small village in Vestby Municipality in Viken county, Norway.
-
C.
Oslo TMA
Oslo TMA is a controlled terminal maneuvering area of Norwegian airspace surrounding Oslo, managing arriving and departing air traffic for the region’s main airports.
-
D.
Bergen TMA
Bergen TMA is a controlled terminal airspace sector in western Norway that manages arriving and departing traffic for the Bergen area’s airports.
-
E.
Oslo East
Oslo East is the eastern part of Norway’s capital city, often associated with working-class neighborhoods, cultural diversity, and a strong local football supporter culture.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a704e2a48190acb55f77a2124412 |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 6 p.m.