Triple
T18682145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajka |
E456759
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Veszprém County |
—
|
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: Veszprém County | Statement: [Ajka, locatedIn, Veszprém County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veszprém County Context triple: [Ajka, locatedIn, Veszprém County]
-
A.
Veszprém County
chosen
Veszprém County is an administrative region in western Hungary known for its historic city of Veszprém and its location along the northern shore of Lake Balaton.
-
B.
Heves County
Heves County is an administrative region in northern Hungary known for its natural landscapes, including part of the Mátra mountain range, and historic towns such as Eger.
-
C.
Trencsén County
Trencsén County was a historic administrative county of the Kingdom of Hungary, located in what is now northwestern Slovakia.
-
D.
Pozsony County
Pozsony County was a historic administrative region of the Kingdom of Hungary centered on the city now known as Bratislava.
-
E.
Zala County
Zala County is an administrative region in southwestern Hungary known for its rolling hills, thermal spas, and proximity to Lake Balaton and the Croatian border.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2906ec8190ad8db8e3ae6b2945 |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.