Triple
T6195591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magura National Park |
E138500
|
entity |
| Predicate | hasMainSettlementNearby |
P3883
|
FINISHED |
| Object | Gorlice |
E25217
|
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: Gorlice | Statement: [Magura National Park, hasMainSettlementNearby, Gorlice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorlice Context triple: [Magura National Park, hasMainSettlementNearby, Gorlice]
-
A.
Gorlice
chosen
Gorlice is a historic town in southern Poland known for its role in the World War I Battle of Gorlice–Tarnów and its early oil industry.
-
B.
Kraśnik
Kraśnik is a town in eastern Poland known for its historical architecture and location within the Lublin region.
-
C.
Czorsztyn
Czorsztyn is a small village in southern Poland known for its picturesque lakeside setting on the Dunajec River and the ruins of a medieval castle overlooking the Pieniny Mountains.
-
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.
Tarnobrzeg
Tarnobrzeg is a city in southeastern Poland known historically for its sulfur mining industry and location along the Vistula River.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0624571508190bd273b4a051fbe41 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fb2378081909f454539f82a0975 |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:20 p.m.