Triple
T13296180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vistula basin |
E316687
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Tarnobrzeg |
—
|
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: Tarnobrzeg | Statement: [Vistula basin, containsCity, Tarnobrzeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarnobrzeg Context triple: [Vistula basin, containsCity, Tarnobrzeg]
-
A.
Tarnobrzeg
chosen
Tarnobrzeg is a city in southeastern Poland known historically for its sulfur mining industry and location along the Vistula River.
-
B.
Targówek
Targówek is a residential district in the northeastern part of Warsaw, Poland, known for its large housing estates, green areas, and growing transport links to the city center.
-
C.
Krotoszyn
Krotoszyn is a historic town in west-central Poland known for its medieval origins and changing political affiliations, including periods under Prussian and German rule.
-
D.
Hrubieszów
Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
-
E.
Brzesko
Brzesko is a town in southern Poland known for its historical architecture and regional brewing traditions.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99079c8508190b6208db9affcbc0e |
completed | April 11, 2026, 12:06 a.m. |
Created at: April 9, 2026, 9:28 p.m.