Triple

T13110201
Position Surface form Disambiguated ID Type / Status
Subject Rho E310948 entity
Predicate hasMetropolitanArea P40 FINISHED
Object Milan metropolitan area E282022 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: Milan metropolitan area | Statement: [Rho, hasMetropolitanArea, Milan metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan metropolitan area
Context triple: [Rho, hasMetropolitanArea, 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 municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • E. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f0ff20081909f277d9c8dc8b043 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9:05 p.m.