Triple

T21699484
Position Surface form Disambiguated ID Type / Status
Subject Mediaset E535616 entity
Predicate headquartersLocation P62 FINISHED
Object Cologno Monzese 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: Cologno Monzese | Statement: [Mediaset, headquartersLocation, Cologno Monzese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cologno Monzese
Context triple: [Mediaset, headquartersLocation, Cologno Monzese]
  • A. Cologno Monzese chosen
    Cologno Monzese is a suburban town in northern Italy known for hosting major television and media studios near Milan.
  • B. Melegnano
    Melegnano is a town in the Lombardy region of northern Italy, historically notable as the site of major Renaissance-era battles including the Battle of Marignano.
  • C. Buccinasco
    Buccinasco is a suburban municipality in northern Italy located just southwest of Milan, known for its residential character and proximity to the Lombard capital.
  • D. Olgiate Comasco
    Olgiate Comasco is a town and municipality in the Lombardy region of northern Italy, situated near the city of Como and close to the Swiss border.
  • E. Bianzano
    Bianzano is a small municipality in the Lombardy region of northern Italy, known for its medieval castle and scenic position near Lake Iseo.
  • 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_69e0c46a6ee481908836e1420fb78c9b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef9b7de9888190bbca7717a32f9888 completed April 27, 2026, 5:23 p.m.
Created at: April 16, 2026, 6:45 p.m.