Triple
T13083953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warta |
E310280
|
entity |
| Predicate | sourceLocation |
P40
|
FINISHED |
| Object | Kromołów |
E471345
|
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: Kromołów | Statement: [Warta, sourceLocation, Kromołów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kromołów Context triple: [Warta, sourceLocation, Kromołów]
-
A.
Kromołów
chosen
Kromołów is a historic district of the city of Zawiercie in southern Poland, known as the place where the Warta River begins.
-
B.
Mikołów
Mikołów is a historic town in southern Poland known for its traditional Silesian character and proximity to the regional capital, Katowice.
-
C.
Krasnobród
Krasnobród is a small town in southeastern Poland known for its historical role in World War II and as a local tourist and spa destination in the Roztocze region.
-
D.
Sułów
Sułów is a village in eastern Poland located within Zamość County in the Lublin Voivodeship.
-
E.
Korczyna
Korczyna is a village in southeastern Poland, known as a local administrative and residential center within the Subcarpathian region.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981361e8c819099376435aa3a7aa3 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c78f36d88190a39f407c5d8dbc0d |
completed | May 10, 2026, 5:59 p.m. |
Created at: April 9, 2026, 9:02 p.m.