Triple
T6619421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larvik |
E149637
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Vestfold |
E94296
|
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: Vestfold | Statement: [Larvik, locatedIn, Vestfold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vestfold Context triple: [Larvik, locatedIn, Vestfold]
-
A.
Agder
Agder is a county in southern Norway known for its long coastline, maritime heritage, and popular coastal towns and islands.
-
B.
Vestfold og Telemark
chosen
Vestfold og Telemark is a former county in southeastern Norway known for its coastal towns, industrial heritage, and varied landscapes from fjords to inland forests and mountains.
-
C.
Aust-Agder
Aust-Agder was a former county in southern Norway known for its coastal towns, forests, and role in the country’s maritime and timber industries.
-
D.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
-
E.
Hordaland
Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af5ca97481909f8a7dc47249b4d3 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8341cd2088190835992e0635d1b4e |
completed | March 28, 2026, 8:03 p.m. |
Created at: March 27, 2026, 1:58 p.m.