Triple
T22234275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kokemäenjoki |
E549547
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Kokemäki |
—
|
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: Kokemäki | Statement: [Kokemäenjoki, passesThrough, Kokemäki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kokemäki Context triple: [Kokemäenjoki, passesThrough, Kokemäki]
-
A.
Kokemäki
chosen
Kokemäki is a small town and municipality in the Satakunta region of western Finland, known for its location along the Kokemäenjoki River and its historical roots dating back to medieval times.
-
B.
Luumäki
Luumäki is a rural municipality in South Karelia, southeastern Finland, known for its forests, lakes, and historical significance.
-
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.
Kangasala
Kangasala is a Finnish town and municipality in the Pirkanmaa region, known for its scenic ridge landscapes and lakes.
-
E.
Tammerkoski
Tammerkoski is a rapid-flowing channel in Tampere, Finland, that connects two lakes and historically powered the city’s industrial development.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf61504819093e70bee4c575d1c |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.