Triple
T22226386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcode district |
E549348
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | Oslo waterfront |
—
|
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 waterfront | Statement: [Barcode district, locatedOn, Oslo waterfront]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo waterfront Context triple: [Barcode district, locatedOn, Oslo waterfront]
-
A.
Fredrikstad waterfront
Fredrikstad waterfront is a scenic urban riverside area in the Norwegian city of Fredrikstad, known for its historic architecture, promenades, and views along the Glomma River.
-
B.
Aker Brygge
chosen
Aker Brygge is a popular waterfront district in Oslo known for its modern architecture, restaurants, shops, and vibrant harbor promenade.
-
C.
Lyngseidet
Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
-
D.
Marienlyst, Oslo
Marienlyst, Oslo is a neighborhood in Norway’s capital city best known as the long-time home of the Norwegian Broadcasting Corporation’s main facilities.
-
E.
Akerselva riverwalk
Akerselva riverwalk is a scenic urban riverside path in Oslo, Norway, known for its waterfalls, historic industrial buildings, street art, and popular walking and cycling routes.
- 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_69e11e403d6481909a94d0aaf157f6ef |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bee8de8819091ec5d14ea057f9e |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.