Triple
T21312887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bøelva |
E525387
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | no:Bøelva |
—
|
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: no:Bøelva | Statement: [Bøelva, hasNameInLanguage, no:Bøelva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: no:Bøelva Context triple: [Bøelva, hasNameInLanguage, no:Bøelva]
-
A.
Bøelva
chosen
Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
-
B.
Bø
Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
-
C.
Bø
Bø is a small town in southern Norway known for its scenic landscapes, outdoor recreation, and role as a local commercial and educational center.
-
D.
Bøler
Bøler is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its post-war apartment blocks, green surroundings, and access to the Østmarka forest.
-
E.
Bøur
Bøur is a small, picturesque village on the Faroe Islands known for its traditional turf-roofed houses and scenic views of nearby islets and sea cliffs.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75dcb45f08190a9bcaa366964a2cb |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 4:25 p.m.