Triple

T15630565
Position Surface form Disambiguated ID Type / Status
Subject Titular Archbishop of Belcastro E375799 entity
Predicate isLocatedIn P40 FINISHED
Object Belcastro E1169293 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: Belcastro | Statement: [Titular Archbishop of Belcastro, isLocatedIn, Belcastro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belcastro
Context triple: [Titular Archbishop of Belcastro, isLocatedIn, Belcastro]
  • A. Belcastro chosen
    Belcastro is a titular archiepiscopal see of the Catholic Church, historically associated with a former diocese in southern Italy.
  • B. Castelbuono
    Castelbuono is a historic medieval town in Sicily, Italy, renowned for its well-preserved castle, traditional architecture, and location within the Madonie mountain region.
  • C. Villarosa
    Villarosa is a small municipality in the Province of Enna in central Sicily, Italy, known for its rural character and traditional Sicilian culture.
  • D. Loiano
    Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
  • E. Montefortino
    Montefortino is a small historic town in Italy’s Marche region, known for its scenic Apennine mountain setting and traditional rural 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb536348190b93ed3c178d1ffb8 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ed079e48190b86ad7b66755fc1c completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:14 a.m.