Triple
T21769613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvi Listhaug |
E537388
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Ørskog |
—
|
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: Ørskog | Statement: [Sylvi Listhaug, placeOfBirth, Ørskog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ørskog Context triple: [Sylvi Listhaug, placeOfBirth, Ørskog]
-
A.
Ørskog
chosen
Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
-
B.
Eidsvåg
Eidsvåg is a village in Møre og Romsdal county, Norway, known for its fjord-side location and role as a local service and industrial hub.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Orkdal
Orkdal was a former municipality in Trøndelag county, Norway, known for its central location in the Orkdalen valley and later incorporation into the larger Orkland municipality.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031ad76848190b2c7a05d091b7faf |
completed | April 28, 2026, 4:03 a.m. |
Created at: April 16, 2026, 6:51 p.m.