Triple

T10309584
Position Surface form Disambiguated ID Type / Status
Subject Hajdú-Bihar County E241851 entity
Predicate containsCity P294 FINISHED
Object Balmazújváros E823307 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: Balmazújváros | Statement: [Hajdú-Bihar County, containsCity, Balmazújváros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balmazújváros
Context triple: [Hajdú-Bihar County, containsCity, Balmazújváros]
  • A. Balmazújváros chosen
    Balmazújváros is a town in eastern Hungary known for its agricultural surroundings and location near the Hortobágy National Park.
  • B. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • C. Dombóvár
    Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna County.
  • D. Törökbálint
    Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
  • E. Nagykőrös
    Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32a18ac81909b4efd8c1ba3e113 completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69f64b78e7ec819093e5e631197ed295 completed May 2, 2026, 7:07 p.m.
Created at: April 6, 2026, 11:47 a.m.