Triple
T7761387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strängnäs |
E176028
|
entity |
| Predicate | isPartOf |
P10
|
FINISHED |
| Object | Strängnäs Municipality |
E176028
|
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: Strängnäs Municipality | Statement: [Strängnäs, isPartOf, Strängnäs Municipality]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strängnäs Municipality Context triple: [Strängnäs, isPartOf, Strängnäs Municipality]
-
A.
Strängnäs
chosen
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
B.
Bollnäs Municipality
Bollnäs Municipality is a local government area in east-central Sweden known for its lakes, forests, and the town of Bollnäs as its administrative center.
-
C.
Gnesta Municipality
Gnesta Municipality is a local government area in Södermanland County, Sweden, known for its small-town character, lakes, and proximity to the Stockholm region.
-
D.
Nykvarn Municipality
Nykvarn Municipality is a small municipality in Stockholm County, Sweden, known for its rural character, forests, and lakes west of Stockholm.
-
E.
Nässjö
Nässjö is a small Swedish town in Jönköping County known as a regional railway hub and service center in southern Sweden.
- 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_69c69962923c8190ac74d28b4f9fe0a0 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c704036c588190a441e56c738cc309 |
completed | March 27, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7d658888190af97b83127086a2b |
completed | March 29, 2026, 6:33 a.m. |
Created at: March 27, 2026, 4:09 p.m.