Triple

T19689713
Position Surface form Disambiguated ID Type / Status
Subject Monza railway station E472801 entity
Predicate near P350 FINISHED
Object Monza Park 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 Park | Statement: [Monza railway station, near, Monza Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monza Park
Context triple: [Monza railway station, near, Monza Park]
  • A. Royal Park of Monza chosen
    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.
  • B. Monza
    Monza is a historic city in northern Italy renowned for its royal villa and the Autodromo Nazionale Monza Formula One racing circuit.
  • C. Rumuola Motor Park
    Rumuola Motor Park is a major public transport hub in the Rumuola area of Port Harcourt, Nigeria, serving as a key boarding and transit point for commuters and intercity travelers.
  • D. 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.
  • E. Mugello
    Mugello is a historic rural region in northern Tuscany, Italy, known for its rolling hills, medieval villages, and cultural heritage.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6420f1a0c8190ae59aa0ab3ff2802 completed April 20, 2026, 3:11 p.m.
Created at: April 10, 2026, 1:45 p.m.