Triple
T16262728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nesodden |
E394792
|
entity |
| Predicate | partOfMetropolitanArea |
P294
|
FINISHED |
| Object | Oslo metropolitan area |
E229565
|
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: Oslo metropolitan area | Statement: [Nesodden, partOfMetropolitanArea, Oslo metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo metropolitan area Context triple: [Nesodden, partOfMetropolitanArea, Oslo metropolitan area]
-
A.
Greater Oslo Region
chosen
The Greater Oslo Region is the metropolitan area surrounding Norway’s capital, encompassing Oslo and its neighboring municipalities as a unified economic and commuter region.
-
B.
Bergens
The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
-
C.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
D.
Oslo
Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
-
E.
Trondheim
Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c5583c8190901e892238cf8dbd |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ecc2b4c8190ac9654ac826f198e |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:04 a.m.