Triple

T19794569
Position Surface form Disambiguated ID Type / Status
Subject Church of San Maurizio E475506 entity
Predicate locatedIn P40 FINISHED
Object Monza 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: Monza | Statement: [Church of San Maurizio, locatedIn, Monza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monza
Context triple: [Church of San Maurizio, locatedIn, Monza]
  • A. Monza chosen
    Monza is a historic city in northern Italy renowned for its royal villa and the Autodromo Nazionale Monza Formula One racing circuit.
  • B. Mugello
    Mugello is a historic rural region in northern Tuscany, Italy, known for its rolling hills, medieval villages, and cultural heritage.
  • C. Imola
    Imola is a historic city in Italy’s Emilia-Romagna region, best known for its Formula One racing circuit, the Autodromo Enzo e Dino Ferrari.
  • D. Royal Park of Monza
    The Royal Park of Monza is a vast historic landscaped park in Monza, Italy, renowned as one of Europe’s largest enclosed parks and for hosting the Monza Formula 1 circuit.
  • E. Monza Circuit
    Monza Circuit is a historic Italian motorsport race track, best known as the high-speed home of the Formula One Italian Grand Prix.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c5a7d48190b2a384f768d13750 completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.