Triple

T9821879
Position Surface form Disambiguated ID Type / Status
Subject Bács-Kiskun County E238550 entity
Predicate hasCity P316 FINISHED
Object Kiskunfélegyháza E418702 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: Kiskunfélegyháza | Statement: [Bács-Kiskun County, hasCity, Kiskunfélegyháza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiskunfélegyháza
Context triple: [Bács-Kiskun County, hasCity, Kiskunfélegyháza]
  • A. Kiskunfélegyháza chosen
    Kiskunfélegyháza is a town in central Hungary known for its historical market-town character and location in the Great Hungarian Plain.
  • B. Kisújszállás
    Kisújszállás is a small town in eastern Hungary known for its agricultural surroundings and location on the Great Hungarian Plain.
  • C. Bicske
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • 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. Kőszeg
    Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3147ecc81908cfca84c05a367d9 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc7ce1908190a5131ef238541f0d completed April 5, 2026, 2:44 a.m.
Created at: March 30, 2026, 8:31 p.m.