Triple

T15250583
Position Surface form Disambiguated ID Type / Status
Subject Trenord E364507 entity
Predicate operatesInMetropolitanArea P5322 FINISHED
Object Milan metropolitan 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 metropolitan area | Statement: [Trenord, operatesInMetropolitanArea, Milan metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milan metropolitan area
Context triple: [Trenord, operatesInMetropolitanArea, Milan metropolitan 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. 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.
  • C. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • D. Milan
    Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • E. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f62b9c8190b9ad40e2d1912b63 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01de4ccc8190aeac4a6c1ffc08d9 completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 3:13 a.m.