Triple
T6209121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Søndre Nordstrand |
E138821
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mortensrud |
E161037
|
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: Mortensrud | Statement: [Søndre Nordstrand, contains, Mortensrud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mortensrud Context triple: [Søndre Nordstrand, contains, Mortensrud]
-
A.
Mortensrud
chosen
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
B.
Gjerdrum
Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
-
C.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
D.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
E.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0628850bc819080a26c5e05a1d29f |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ad5851b481908242f6d88a78a08a |
completed | March 28, 2026, 10:28 a.m. |
Created at: March 22, 2026, 4:21 p.m.