Triple
T10297374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västmanland County |
E241527
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Västmanlands län |
E241527
|
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: Västmanlands län | Statement: [Västmanland County, nativeName, Västmanlands län]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Västmanlands län Context triple: [Västmanland County, nativeName, Västmanlands län]
-
A.
Västmanland
Västmanland is a historic province in central Sweden known for its forests, lakes, and long tradition of mining and metallurgy.
-
B.
Västmanland County
chosen
Västmanland County is an administrative region in central Sweden known for its mix of industrial towns, forests, and lakes.
-
C.
Kalmar län
Kalmar län is a county in southeastern Sweden known for its Baltic Sea coastline, historic towns, and the island of Öland.
-
D.
Södermanland County
Södermanland County is an administrative region in east-central Sweden known for its mix of coastal landscapes, forests, and historic towns such as Nyköping and Eskilstuna.
-
E.
Jämtland County
Jämtland County is a large, sparsely populated region in central Sweden known for its mountains, forests, and popular outdoor tourism areas.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2ebd258819099fadddcd13099fc |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d2cc9c48190bc36f6a4f8144b7f |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:43 a.m.