Triple
T19802383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midt-Telemark |
E475714
|
entity |
| Predicate | hasAdministrativeCentre |
P1474
|
FINISHED |
| Object | Bø |
—
|
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: Bø | Statement: [Midt-Telemark, hasAdministrativeCentre, Bø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bø Context triple: [Midt-Telemark, hasAdministrativeCentre, Bø]
-
A.
Bø
Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
-
B.
Bø
chosen
Bø is a small town in southern Norway known for its scenic landscapes, outdoor recreation, and role as a local commercial and educational center.
-
C.
Bøstad
Bøstad is a small village in the Lofoten archipelago of Nordland county, Norway, known for its scenic coastal landscape and proximity to Viking-era historical sites.
-
D.
Bøelva
Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
-
E.
Bojnord
Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654257cb4819096fb2aa5d1f7fbb0 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.