Triple
T5658167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akersgata area, Oslo |
E124669
|
entity |
| Predicate | street |
P959
|
FINISHED |
| Object | Akersgata |
E518506
|
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: Akersgata | Statement: [Akersgata area, Oslo, street, Akersgata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akersgata Context triple: [Akersgata area, Oslo, street, Akersgata]
-
A.
Akersgata
chosen
Akersgata is a central street in Oslo, Norway, known for running through the city’s political and media district and hosting several important government and newspaper buildings.
-
B.
Hedmarksgata
Hedmarksgata is a street located in the Vålerenga neighborhood of Oslo, Norway.
-
C.
Vålerenggata
Vålerenggata is a street located in the Vålerenga neighborhood of Oslo, Norway, known for its traditional wooden houses and historic urban character.
-
D.
Birger Jarlsgatan
Birger Jarlsgatan is a major central street in Stockholm, Sweden, known for its upscale shops, offices, and role as a key thoroughfare through the Östermalm district.
-
E.
Tegnergatan
Tegnergatan is a central street in Stockholm, Sweden, known for connecting several major thoroughfares and passing through the Vasastan and Norrmalm districts.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022fd9b148190bd4aa9c43500949f |
completed | March 22, 2026, 5:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097d7e0fc81909f051f8789ef9fb9 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:42 p.m.