Triple

T21326147
Position Surface form Disambiguated ID Type / Status
Subject University of Milano-Bicocca E525762 entity
Predicate city P40 FINISHED
Object Milan 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 | Statement: [University of Milano-Bicocca, city, Milan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan
Context triple: [University of Milano-Bicocca, city, Milan]
  • A. Milan
    Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • B. Milan chosen
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • C. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • D. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • E. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • 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_69e0b51b90788190a4dd823d962626da completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7ab49aa48819083b3793657903216 completed April 21, 2026, 4:52 p.m.
Created at: April 16, 2026, 4:41 p.m.