Triple
T20846346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajka District |
E513234
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Veszprémfajsz |
—
|
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: Veszprémfajsz | Statement: [Ajka District, containsSettlement, Veszprémfajsz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veszprémfajsz Context triple: [Ajka District, containsSettlement, Veszprémfajsz]
-
A.
Veszprémfajsz
chosen
Veszprémfajsz is a small village in Veszprém County in western Hungary, situated near Lake Balaton.
-
B.
Vasvár
Vasvár is a small historic town in western Hungary known for its medieval heritage and role as a former county seat.
-
C.
Fertőd
Fertőd is a small town in northwestern Hungary best known for the grand Esterházy Palace, often called the “Hungarian Versailles.”
-
D.
Füzesabony
Füzesabony is a small town in northeastern Hungary known as a regional railway junction and gateway to the Bükk and Mátra regions.
-
E.
Tiszavasvári
Tiszavasvári is a town in northeastern Hungary known for its agricultural surroundings and location within the Northern Great Plain region.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34ffb588190881953a0480b29a8 |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.