Triple

T2018376
Position Surface form Disambiguated ID Type / Status
Subject Umberto I of Italy E44047 entity
Predicate deathPlace P21 FINISHED
Object Monza E107899 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: Monza | Statement: [Umberto I of Italy, deathPlace, Monza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monza
Context triple: [Umberto I of Italy, deathPlace, 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. 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.
  • C. Secchia
    The Secchia is a river in northern Italy that flows through the Emilia-Romagna region and is one of the main tributaries contributing to the Po River system.
  • D. Torino Porta Susa
    Torino Porta Susa is a major high-speed and regional railway hub in Turin, Italy, serving as one of the city’s principal train stations.
  • E. Montella, Italy
    Montella, Italy is a small town in the Campania region of southern Italy, known for its mountainous landscape and traditional chestnut production.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8ce71788190ac21beff10b08122 completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe88e8881909f2e64ebe23b6d1f completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:38 p.m.