Triple
T17804334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lindesberg Municipality |
E444515
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Lindesberg |
—
|
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: Lindesberg | Statement: [Lindesberg Municipality, administrativeCenter, Lindesberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lindesberg Context triple: [Lindesberg Municipality, administrativeCenter, Lindesberg]
-
A.
Lindesberg
chosen
Lindesberg is a small historic town in central Sweden known for its mining heritage and lakeside setting.
-
B.
Lindhagen
Lindhagen is a Swedish surname most notably associated with the politician and social reformer Carl Lindhagen.
-
C.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
D.
Tingsryd
Tingsryd is a small locality and municipality in southern Sweden known for its rural landscapes, lakes, and traditional Swedish countryside character.
-
E.
Strömholm
Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48802bcfc8190a138164d11081ab8 |
completed | April 19, 2026, 7:45 a.m. |
Created at: April 10, 2026, 10:14 a.m.