Triple
T20708287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tippeligaen |
E508962
|
entity |
| Predicate | formerSponsorshipName |
P15098
|
FINISHED |
| Object | Tippeligaen |
—
|
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: Tippeligaen | Statement: [Tippeligaen, formerSponsorshipName, Tippeligaen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tippeligaen Context triple: [Tippeligaen, formerSponsorshipName, Tippeligaen]
-
A.
Tippeligaen
chosen
Tippeligaen was the former sponsored name of Norway’s top-tier professional football league, now known as Eliteserien.
-
B.
Vålerenga
Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
-
C.
Bryne FK
Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
-
D.
Strømsgodset
Strømsgodset is a Norwegian professional football club based in Drammen, best known for competing in the country’s top division, the Eliteserien.
-
E.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
- 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_69e0b4c40ad88190b81f77695366d328 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1952e888190877b79933970f7b0 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:14 p.m.