Triple

T15429053
Position Surface form Disambiguated ID Type / Status
Subject Bresso E369586 entity
Predicate hasTransportConnection P845 FINISHED
Object Milan urban 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 urban area | Statement: [Bresso, hasTransportConnection, Milan urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan urban area
Context triple: [Bresso, hasTransportConnection, Milan urban 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. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • C. Milan
    Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • D. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • E. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec31f4881908b26ff7c381d7bc9 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec4e868819092739e71118d43b0 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 3:21 a.m.