Triple
T11801005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kokkola |
E280624
|
entity |
| Predicate | SwedishName |
P11737
|
FINISHED |
| Object | Karleby |
E215151
|
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: Karleby | Statement: [Kokkola, SwedishName, Karleby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karleby Context triple: [Kokkola, SwedishName, Karleby]
-
A.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
B.
Karlbo
Karlbo is a small locality in Sweden best known as the birthplace of Nobel Prize–winning poet Erik Axel Karlfeldt.
-
C.
Nykarleby
chosen
Nykarleby is a small bilingual coastal town and municipality in western Finland known for its Swedish-speaking majority and location in the Ostrobothnia region.
-
D.
Mjölby
Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
-
E.
Ljungby
Ljungby is a small Swedish town in southern Småland known for its lakeside surroundings, forestry-based economy, and role as a local commercial and cultural center.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a4512c8190b7782e1dee053000 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f13129fa608190b080dc27f8bd7803 |
completed | April 28, 2026, 10:14 p.m. |
Created at: April 8, 2026, 9:42 p.m.