Triple
T21775727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vålerenggata |
E537568
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Vålerenga |
—
|
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: Vålerenga | Statement: [Vålerenggata, locatedIn, Vålerenga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vålerenga Context triple: [Vålerenggata, locatedIn, Vålerenga]
-
A.
Vålerenga
chosen
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
-
B.
Vålerenga Fotball
Vålerenga Fotball is a Norwegian professional football club based in Oslo, known for its passionate fan base and history in the country’s top division.
-
C.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
-
D.
Bryne FK
Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
-
E.
Kongsvinger IL
Kongsvinger IL is a Norwegian sports club best known for its football team, which has competed in the country’s top divisions.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f046291d808190b5111a8d4819909f |
completed | April 28, 2026, 5:31 a.m. |
Created at: April 16, 2026, 6:51 p.m.