Triple

T599655
Position Surface form Disambiguated ID Type / Status
Subject Milan E11464 entity
Predicate airport P1065 FINISHED
Object Orio al Serio Airport E28173 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: Orio al Serio Airport | Statement: [Milan, airport, Orio al Serio Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orio al Serio Airport
Context triple: [Milan, airport, Orio al Serio Airport]
  • A. Ministro Pistarini International Airport
    Ministro Pistarini International Airport is the main international gateway to Buenos Aires and one of Argentina’s busiest and most important airports.
  • B. Turin Airport
    Turin Airport is the main international airport serving the city of Turin and the surrounding Piedmont region in northern Italy.
  • C. Milan Malpensa Airport
    Milan Malpensa Airport is a major international airport serving the Milan metropolitan area in northern Italy and one of the country’s busiest air transport hubs.
  • D. Milan Bergamo Airport chosen
    Milan Bergamo Airport is a major low-cost international airport in northern Italy that serves the Milan metropolitan area and is a key base for Ryanair’s European operations.
  • E. Milan Linate Airport
    Milan Linate Airport is a major city airport serving Milan, Italy, primarily handling domestic and short-haul European flights close to the city center.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d78c0f08190b83ad89062ccb0b9 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a529220bc4819087e9de129139b6ef completed March 2, 2026, 6:07 a.m.
Created at: March 1, 2026, 7:35 p.m.