Triple
T20368126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ÓE |
E496969
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Central Hungary |
—
|
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: Central Hungary | Statement: [ÓE, region, Central Hungary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Central Hungary Context triple: [ÓE, region, Central Hungary]
-
A.
Central Hungary
chosen
Central Hungary is a key administrative and economic region of Hungary that includes the capital city, Budapest, and serves as the country’s primary political and commercial hub.
-
B.
Northern Hungary
Northern Hungary is a region of Hungary known for its industrial cities like Miskolc, historic castles, and the Bükk and Mátra mountain ranges.
-
C.
Eastern Hungary
Eastern Hungary is a geographic region of Hungary that includes major cities such as Debrecen and is known for its plains, cultural heritage, and agricultural significance.
-
D.
Southeastern Hungary
Southeastern Hungary is a largely flat, agricultural region of Hungary known for its rural landscapes, historic towns, and proximity to the Romanian and Serbian borders.
-
E.
Southwestern Hungary
Southwestern Hungary is a geographic region of Hungary bordering Croatia and Slovenia, known for its rolling hills, thermal spas, and historic towns such as Nagykanizsa and Pécs.
- 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678734b188190bb2c5863023f9f8c |
completed | April 20, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:26 a.m.