Triple
T17013958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vas County |
E412769
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Kőszeg |
—
|
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: Kőszeg | Statement: [Vas County, containsSettlement, Kőszeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kőszeg Context triple: [Vas County, containsSettlement, Kőszeg]
-
A.
Kőszeg
chosen
Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
-
B.
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.
-
C.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
D.
Mezőkeresztes
Mezőkeresztes is a town in northeastern Hungary historically notable as the site of a major 1596 battle between Ottoman and Habsburg forces.
-
E.
Szécsény
Szécsény is a historic town in northern Hungary known for its medieval architecture and role as a regional center in Nógrád County.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d47e64f081908f43870c7564d0ae |
completed | April 18, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:33 a.m.