Triple

T19689664
Position Surface form Disambiguated ID Type / Status
Subject AC Monza E472800 entity
Predicate basedInMetropolitanArea P294 FINISHED
Object Milan metropolitan area 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: Milan metropolitan area | Statement: [AC Monza, basedInMetropolitanArea, Milan metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan metropolitan area
Context triple: [AC Monza, basedInMetropolitanArea, Milan metropolitan area]
  • A. Metropolitan City of Milan chosen
    The Metropolitan City of Milan is an Italian administrative region centered on the city of Milan, encompassing its surrounding municipalities and serving as a major hub for finance, fashion, industry, and transportation.
  • B. Rome metropolitan area
    The Rome metropolitan area is a regional urban and economic center in northwestern Georgia, anchored by the city of Rome and its surrounding communities.
  • C. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • D. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • E. Milan
    Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • 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.