Triple
T18264803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ungar |
E437455
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Ungár |
—
|
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: Ungár | Statement: [Ungar, hasVariant, Ungár]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ungár Context triple: [Ungar, hasVariant, Ungár]
-
A.
Ungar
chosen
Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
-
B.
Poroszló
Poroszló is a village in northern Hungary situated near Lake Tisza, known for its natural surroundings and eco-tourism opportunities.
-
C.
Hungarica
Hungarica refers to publications and documents related to Hungary or Hungarians, regardless of where they were produced.
-
D.
Zala
Zala is a river in western Hungary that flows into Lake Balaton and lends its name to the surrounding Zala region.
-
E.
Ispánk
Ispánk is a small rural village in western Hungary, situated within the historic and scenic Őrség region known for its traditional architecture and natural landscapes.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff79851481909a4bbeb14fb00647 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.