Triple
T22312909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vimmerby Municipality |
E551565
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Vimmerby |
—
|
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: Vimmerby | Statement: [Vimmerby Municipality, namedAfter, Vimmerby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vimmerby Context triple: [Vimmerby Municipality, namedAfter, Vimmerby]
-
A.
Vimmerby
chosen
Vimmerby is a small town in southern Sweden best known as the birthplace of beloved children's author Astrid Lindgren and for its associated literary tourism.
-
B.
Söderhamn
Söderhamn is a coastal town in east-central Sweden known for its historical wooden architecture and role as the administrative and commercial center of the surrounding region.
-
C.
Hässleholm
Hässleholm is a town in southern Sweden’s Skåne County known as a regional railway hub and service center.
-
D.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
E.
Sandviken
Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15750f76c81909d6f788928f503f1 |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.