Triple
T22560325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venta River |
E557794
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Kuršėnai |
—
|
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: Kuršėnai | Statement: [Venta River, flowsThrough, Kuršėnai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuršėnai Context triple: [Venta River, flowsThrough, Kuršėnai]
-
A.
Kuršėnai
chosen
Kuršėnai is a town in northern Lithuania known for its pottery traditions and location along the Venta River.
-
B.
Švenčionys
Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
-
C.
Šalčininkai
Šalčininkai is a town in southeastern Lithuania known for its multicultural population and location near the Belarusian border.
-
D.
Šilutė
Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
-
E.
Kelmė
Kelmė is a small town in northern Lithuania known as the administrative center of Kelmė District Municipality and for its historic manor and surrounding rural landscapes.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7c914881909584c46ae323c779 |
completed | April 29, 2026, 1:31 a.m. |
Created at: April 16, 2026, 8:52 p.m.