Triple
T7075216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Hanshaugen |
E164799
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bolteløkka |
E551707
|
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: Bolteløkka | Statement: [St. Hanshaugen, contains, Bolteløkka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bolteløkka Context triple: [St. Hanshaugen, contains, Bolteløkka]
-
A.
Bolteløkka
chosen
Bolteløkka is a residential neighborhood in central Oslo, Norway, known for its historic apartment buildings, schools, and proximity to St. Hanshaugen Park.
-
B.
Risløkka
Risløkka is a residential neighborhood in Oslo, Norway, known for its mix of housing, local services, and proximity to major transport routes.
-
C.
Rodeløkka
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.
-
D.
Skøyen
Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
-
E.
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.
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ce3d3c81908cbb912b256aadbf |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79468c7688190bf10433f05e77574 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:40 p.m.