Triple
T10092742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Hungary |
E215782
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Mezőkövesd |
E1001742
|
NE FINISHED |
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: Mezőkövesd | Statement: [Northern Hungary, containsTown, Mezőkövesd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mezőkövesd Context triple: [Northern Hungary, containsTown, Mezőkövesd]
-
A.
Mezőkövesd
chosen
Mezőkövesd is a town in northeastern Hungary known for its Matyó folk art traditions and cultural heritage.
-
B.
Mezőkeresztes
Mezőkeresztes is a town in northeastern Hungary historically notable as the site of a major 1596 battle between Ottoman and Habsburg forces.
-
C.
Kecskemét
Kecskemét is a city in central Hungary known for its Art Nouveau architecture, cultural institutions, and role as an administrative and economic center of the region.
-
D.
Békéscsaba
Békéscsaba is a city in southeastern Hungary known as the administrative center of Békés County and for its cultural and culinary traditions, including its famous sausage.
-
E.
Kiskőrös
Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd05c3c0c8190927580717429a4e5 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68e99c2608190b923ca8a9178fea2 |
completed | May 2, 2026, 11:54 p.m. |
Created at: March 30, 2026, 9:01 p.m.