Triple
T20815741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zirc |
E512431
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Bakonybél |
—
|
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: Bakonybél | Statement: [Zirc, locatedNear, Bakonybél]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bakonybél Context triple: [Zirc, locatedNear, Bakonybél]
-
A.
Bakonybél
chosen
Bakonybél is a small Hungarian village in the Bakony region, known for its Benedictine monastery, forested surroundings, and role as a center of nature tourism and hiking.
-
B.
Bonyhád
Bonyhád is a town in southern Hungary known as an important local center within Tolna County.
-
C.
Bóly
Bóly is a small town in southern Hungary known for its agricultural surroundings and location within Baranya County.
-
D.
Bácska
Bácska is a historical region in the Pannonian Plain, today divided between northern Serbia and southern Hungary, known for its multicultural population and agricultural importance.
-
E.
Bicske
Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d5a514819093d1a18626de8857 |
completed | April 21, 2026, 12:20 a.m. |
Created at: April 16, 2026, 12:41 p.m.