Triple
T16811794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FK Gjøvik-Lyn |
E408630
|
entity |
| Predicate | hasFanBaseIn |
P897
|
FINISHED |
| Object | Innlandet |
E65742
|
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: Innlandet | Statement: [FK Gjøvik-Lyn, hasFanBaseIn, Innlandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Innlandet Context triple: [FK Gjøvik-Lyn, hasFanBaseIn, Innlandet]
-
A.
Innlandet
chosen
Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
-
B.
Innlandet
Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
-
C.
Hadeland
Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
-
D.
Jørpeland
Jørpeland is a town in Rogaland county, Norway, known as a local industrial and service hub and a gateway to the nearby Lysefjord and Preikestolen (Pulpit Rock).
-
E.
Haugalandet
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
- 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_6a00dbfb781881908f4d56f523e78f7a |
completed | May 10, 2026, 7:26 p.m. |
Created at: April 10, 2026, 5:23 a.m.