Triple
T6592410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinsen |
E148392
|
entity |
| Predicate | hasNearbyNeighborhood |
P350
|
FINISHED |
| Object | Rodeløkka |
E540471
|
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: Rodeløkka | Statement: [Sinsen, hasNearbyNeighborhood, Rodeløkka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rodeløkka Context triple: [Sinsen, hasNearbyNeighborhood, Rodeløkka]
-
A.
Rodeløkka
chosen
Rodeløkka is a historic residential neighborhood in Oslo, Norway, known for its wooden houses, narrow streets, and close-knit, village-like atmosphere within the inner city.
-
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.
Bolteløkka
Bolteløkka is a residential neighborhood in central Oslo, Norway, known for its historic apartment buildings, schools, and proximity to St. Hanshaugen Park.
-
D.
Kjelsås
Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
-
E.
Skøyen
Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
- 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aece1f848190a11676e072afb002 |
completed | March 27, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbba656c81909c3876a8f2f7300e |
completed | March 27, 2026, 6:26 p.m. |
Created at: March 27, 2026, 1:55 p.m.