Triple
T21476232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Frösjön |
E529867
|
entity |
| Predicate | hasShorelineSettlement |
P969
|
FINISHED |
| Object | Gnesta |
—
|
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: Gnesta | Statement: [Lake Frösjön, hasShorelineSettlement, Gnesta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gnesta Context triple: [Lake Frösjön, hasShorelineSettlement, Gnesta]
-
A.
Gnesta
chosen
Gnesta is a small town in Södermanland County, Sweden, known for its lakeside setting and role as a local commercial and transport hub.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
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.
Stavsnäs
Stavsnäs is a coastal village and locality in Värmdö Municipality in Stockholm County, Sweden, known as a key ferry and boating hub in the Stockholm archipelago.
-
E.
Ronneby
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1737f881908ef7889e9568a4d3 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:20 p.m.