Triple

T10092651
Position Surface form Disambiguated ID Type / Status
Subject Borsod-Abaúj-Zemplén County E215779 entity
Predicate namedAfter P63 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: [Borsod-Abaúj-Zemplén County, namedAfter, Abaúj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abaúj
Context triple: [Borsod-Abaúj-Zemplén County, namedAfter, 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_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_69d2e591be44819094623fd11f6fccdb completed April 5, 2026, 10:43 p.m.
Created at: March 30, 2026, 9:01 p.m.