Triple
T16811788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FK Gjøvik-Lyn |
E408630
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Gjøvik-Lyn |
E408630
|
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: Gjøvik-Lyn | Statement: [FK Gjøvik-Lyn, shortName, Gjøvik-Lyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gjøvik-Lyn Context triple: [FK Gjøvik-Lyn, shortName, Gjøvik-Lyn]
-
A.
FK Gjøvik-Lyn
chosen
FK Gjøvik-Lyn is a Norwegian football club based in the town of Gjøvik, competing in the national league system.
-
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.
Mjøndalen
Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
-
D.
Drøbak-Frogn IL
Drøbak-Frogn IL is a Norwegian sports club best known for its football program, which helped develop future international star Martin Ødegaard in his youth.
-
E.
Tippeligaen
Tippeligaen was the former sponsored name of Norway’s top-tier professional football league, now known as Eliteserien.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2d0793c81909d938ac174a6e63a |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb0f863081908e74dc4a7c91e91d |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:23 a.m.