Triple

T22124751
Position Surface form Disambiguated ID Type / Status
Subject Church of San Francesco Borgia, Catania E546764 entity
Predicate locatedIn P40 FINISHED
Object Catania NE NERFINISHED

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: Catania | Statement: [Church of San Francesco Borgia, Catania, locatedIn, Catania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catania
Context triple: [Church of San Francesco Borgia, Catania, locatedIn, Catania]
  • A. Catania chosen
    Catania is a historic port city on the eastern coast of Sicily, Italy, known for its Baroque architecture and proximity to Mount Etna.
  • B. Palermo
    Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
  • C. Palermo
    Palermo is a municipality in the Huila Department of southern Colombia, known for its agricultural activities and proximity to the departmental capital, Neiva.
  • D. Palermo
    Palermo is an unincorporated community and census-designated place within Upper Township in Cape May County, New Jersey, known for its residential character and proximity to the Jersey Shore.
  • E. Palermo
    Palermo is a 90 nm, low-power, budget-oriented core used in AMD's Sempron line of processors.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e39bf348190b541bfa16a7b71e0 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12980e2488190b58b541c8bee8480 completed April 28, 2026, 9:41 p.m.
Created at: April 16, 2026, 8:31 p.m.