Triple
T19836781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrik Wigström |
E476617
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Ekenäs |
—
|
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: Ekenäs | Statement: [Henrik Wigström, birthPlace, Ekenäs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ekenäs Context triple: [Henrik Wigström, birthPlace, Ekenäs]
-
A.
Ekenäs
chosen
Ekenäs is a coastal town in southern Finland known for its historic wooden architecture and seaside setting.
-
B.
Kangasala
Kangasala is a Finnish town and municipality in the Pirkanmaa region, known for its scenic ridge landscapes and lakes.
-
C.
Kajansi
Kajansi is a township in Uganda located near Kampala, known for its strategic position along the Kampala–Entebbe road and its local market and trading activities.
-
D.
Kullö
Kullö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
-
E.
Karttula
Karttula is a small former municipality in eastern Finland, known for its rural landscapes and location within the Northern Savonia region.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d275608190841b23de167c401e |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.