Triple

T4477928
Position Surface form Disambiguated ID Type / Status
Subject Expo 2015 E100056 entity
Predicate city P40 FINISHED
Object Milan E11464 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 | Statement: [Expo 2015, city, Milan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan
Context triple: [Expo 2015, city, Milan]
  • A. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • B. Milan chosen
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • C. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • D. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • E. Metropolitan City of Milan
    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.
  • 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_69b34553cbe48190afa8ac1cac285b86 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356d9d1d08190b3f9356eefd237dc completed March 13, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b65f40a594819095f2b07e30b5e3dc completed March 15, 2026, 7:26 a.m.
Created at: March 12, 2026, 11:35 p.m.