Triple

T8478123
Position Surface form Disambiguated ID Type / Status
Subject Mecsek Mountains E200445 entity
Predicate hasSettlementNearby P7611 FINISHED
Object Pécsvárad E590458 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: Pécsvárad | Statement: [Mecsek Mountains, hasSettlementNearby, Pécsvárad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pécsvárad
Context triple: [Mecsek Mountains, hasSettlementNearby, Pécsvárad]
  • A. Pécsvárad chosen
    Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
  • B. Gyulafehérvár
    Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
  • C. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • D. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • E. 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.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5216d6481908e25a49bcc2e00cc completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4de95e3081908277c65598f3884a completed April 2, 2026, 11:07 a.m.
Created at: March 30, 2026, 6:12 p.m.