Triple

T10092631
Position Surface form Disambiguated ID Type / Status
Subject Borsod-Abaúj-Zemplén County E215779 entity
Predicate contains P35 FINISHED
Object Tiszaújváros E306629 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: Tiszaújváros | Statement: [Borsod-Abaúj-Zemplén County, contains, Tiszaújváros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiszaújváros
Context triple: [Borsod-Abaúj-Zemplén County, contains, Tiszaújváros]
  • A. Tiszaújváros chosen
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • B. Tiszavasvári
    Tiszavasvári is a town in northeastern Hungary known for its agricultural surroundings and location within the Northern Great Plain region.
  • C. Dunakeszi
    Dunakeszi is a town in Hungary located just north of Budapest, known as a rapidly growing suburban and commuter settlement along the Danube in Pest County.
  • D. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • E. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • 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_69f2802d74f081909c7af34bf266ae01 completed April 29, 2026, 10:03 p.m.
Created at: March 30, 2026, 9:01 p.m.