Triple
T11703987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abov |
E278194
|
entity |
| Predicate | hasNameInHungarian |
P27628
|
FINISHED |
| Object | Abaúj |
E841868
|
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: Abaúj | Statement: [Abov, hasNameInHungarian, Abaúj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abaúj Context triple: [Abov, hasNameInHungarian, Abaúj]
-
A.
Bácska
Bácska is a historical region in the Pannonian Plain, today divided between northern Serbia and southern Hungary, known for its multicultural population and agricultural importance.
-
B.
Borsod
chosen
Borsod is a historical region in northeastern Hungary that once formed its own county and now lends its name to the modern Borsod-Abaúj-Zemplén County.
-
C.
Sajó
Sajó is a river in Central Europe that flows through Slovakia and northeastern Hungary before joining the Tisza River.
-
D.
Tatabánya
Tatabánya is an industrial city in northwestern Hungary known for its mining heritage and role as a regional economic center.
-
E.
Zala
Zala is a river in western Hungary that flows into Lake Balaton and lends its name to the surrounding Zala 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49b1080819096593733ee48a187 |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83525ae081909ee6f3fbb5d37dd7 |
completed | April 27, 2026, 3:40 p.m. |
Created at: April 8, 2026, 9:40 p.m.