Triple

T1626991
Position Surface form Disambiguated ID Type / Status
Subject Milan Malpensa Airport E35167 entity
Predicate serves P98 FINISHED
Object Milan metropolitan area 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 metropolitan area | Statement: [Milan Malpensa Airport, serves, Milan metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan metropolitan area
Context triple: [Milan Malpensa Airport, serves, Milan metropolitan area]
  • A. 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.
  • 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. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • E. Metropolitan City of Turin
    The Metropolitan City of Turin is an Italian administrative region in Piedmont that encompasses the city of Turin and its surrounding municipalities, coordinating local governance, infrastructure, and regional development.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909d2fbe881908451ecd363cc33b0 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6518e07081909c34a363d7ac0f25 completed March 9, 2026, 6:13 a.m.
Created at: March 4, 2026, 7:28 p.m.