Triple
T21297110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oroszlány |
E524952
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object | Oroszlány |
—
|
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: Oroszlány | Statement: [Oroszlány, officialName, Oroszlány]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oroszlány Context triple: [Oroszlány, officialName, Oroszlány]
-
A.
Oroszlány
chosen
Oroszlány is a town in northwestern Hungary known historically for its coal mining and industrial character.
-
B.
Felsőörs
Felsőörs is a village in Veszprém County, Hungary, known for its historic Romanesque church and its location near Lake Balaton.
-
C.
Balvanyos
Balvanyos is a Romanian mountain resort area known for its natural mineral springs, spa facilities, and scenic surroundings in the Eastern Carpathians.
-
D.
Rozsnyó
Rozsnyó is a historic town in present-day Slovakia, known for its medieval center and long-standing cultural significance within the Felvidék (Upper Hungary) region.
-
E.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
- 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385968308190bc9fe5c2bd4598e6 |
completed | April 21, 2026, 8:42 a.m. |
Created at: April 16, 2026, 4:04 p.m.